Namespaces
	detail

	ioutils

Classes
class	AbsImageFilter
	Computes the absolute value of each pixel. More...

class	AbsoluteValueDifferenceImageFilter
	Implements pixel-wise the computation of absolute value difference. More...

class	AcosImageFilter
	Computes the inverse cosine of each pixel. More...

class	AdaptiveHistogramEqualizationImageFilter
	Power Law Adaptive Histogram Equalization. More...

class	AddImageFilter
	Pixel-wise addition of two images. More...

class	AdditiveGaussianNoiseImageFilter
	Alter an image with additive Gaussian white noise. More...

class	AffineTransform
	An affine transformation about a fixed center with translation for a 2D or 3D coordinate. More...

class	AggregateLabelMapFilter
	Collapses all labels into the first label. More...

class	AndImageFilter
	Implements the AND bitwise operator pixel-wise between two images. More...

class	AntiAliasBinaryImageFilter
	A method for estimation of a surface from a binary volume. More...

class	ApproximateSignedDistanceMapImageFilter
	Create a map of the approximate signed distance from the boundaries of a binary image. More...

class	AsinImageFilter
	Computes the sine of each pixel. More...

class	Atan2ImageFilter
	Computes two argument inverse tangent. More...

class	AtanImageFilter
	Computes the one-argument inverse tangent of each pixel. More...

struct	BasicPixelID

class	BilateralImageFilter
	Blurs an image while preserving edges. More...

class	BinaryClosingByReconstructionImageFilter
	binary closing by reconstruction of an image. More...

class	BinaryContourImageFilter
	Labels the pixels on the border of the objects in a binary image. More...

class	BinaryDilateImageFilter
	Fast binary dilation of a single intensity value in the image. More...

class	BinaryErodeImageFilter
	Fast binary erosion of a single intensity value in the image. More...

class	BinaryFillholeImageFilter
	Remove holes not connected to the boundary of the image. More...

class	BinaryGrindPeakImageFilter
	Remove the objects not connected to the boundary of the image. More...

class	BinaryImageToLabelMapFilter
	Label the connected components in a binary image and produce a collection of label objects. More...

class	BinaryMagnitudeImageFilter
	Computes the square root of the sum of squares of corresponding input pixels. More...

class	BinaryMedianImageFilter
	Applies a version of the median filter optimized for binary images. More...

class	BinaryMinMaxCurvatureFlowImageFilter
	Denoise a binary image using min/max curvature flow. More...

class	BinaryMorphologicalClosingImageFilter
	binary morphological closing of an image. More...

class	BinaryMorphologicalOpeningImageFilter
	binary morphological opening of an image. More...

class	BinaryNotImageFilter
	Implements the BinaryNot logical operator pixel-wise between two images. More...

class	BinaryOpeningByReconstructionImageFilter
	binary morphological closing of an image. More...

class	BinaryProjectionImageFilter
	Binary projection. More...

class	BinaryPruningImageFilter
	This filter removes "spurs" of less than a certain length in the input image. More...

class	BinaryReconstructionByDilationImageFilter
	binary reconstruction by dilation of an image More...

class	BinaryReconstructionByErosionImageFilter
	binary reconstruction by erosion of an image More...

class	BinaryThinningImageFilter
	This filter computes one-pixel-wide edges of the input image. More...

class	BinaryThresholdImageFilter
	Binarize an input image by thresholding. More...

class	BinaryThresholdProjectionImageFilter
	BinaryThreshold projection. More...

class	BinomialBlurImageFilter
	Performs a separable blur on each dimension of an image. More...

class	BinShrinkImageFilter
	Reduce the size of an image by an integer factor in each dimension while performing averaging of an input neighborhood. More...

class	BitwiseNotImageFilter
	Implements pixel-wise generic operation on one image. More...

class	BlackTopHatImageFilter
	Black top hat extracts local minima that are smaller than the structuring element. More...

class	BoundedReciprocalImageFilter
	Computes 1/(1+x) for each pixel in the image. More...

class	BoxMeanImageFilter
	Implements a fast rectangular mean filter using the accumulator approach. More...

class	BoxSigmaImageFilter
	Implements a fast rectangular sigma filter using the accumulator approach. More...

class	BSplineDecompositionImageFilter
	Calculates the B-Spline coefficients of an image. Spline order may be from 0 to 5. More...

class	BSplineTransform
	A deformable transform over a bounded spatial domain using a BSpline representation for a 2D or 3D coordinate space. More...

class	BSplineTransformInitializerFilter
	BSplineTransformInitializerFilter is a helper class intended to initialize the control point grid such that it has a physically consistent definition. It sets the transform domain origin, physical dimensions and direction from information obtained from the image. It also sets the mesh size if asked to do so by calling SetTransformDomainMeshSize()before calling InitializeTransform(). More...

class	CannyEdgeDetectionImageFilter
	This filter is an implementation of a Canny edge detector for scalar-valued images. More...

class	CannySegmentationLevelSetImageFilter
	Segments structures in images based on image features derived from pseudo-canny-edges. More...

class	CastImageFilter
	A hybrid cast image filter to convert images to other types of images. More...

class	CenteredTransformInitializerFilter
	CenteredTransformInitializerFilter is a helper class intended to initialize the center of rotation and the translation of Transforms having the center of rotation among their parameters. More...

class	CenteredVersorTransformInitializerFilter
	CenteredVersorTransformInitializerFilter is a helper class intended to initialize the center of rotation, versor, and translation of the VersorRigid3DTransform. More...

class	ChangeLabelImageFilter
	Change Sets of Labels. More...

class	ChangeLabelLabelMapFilter
	Replace the label Ids of selected LabelObjects with new label Ids. More...

class	CheckerBoardImageFilter
	Combines two images in a checkerboard pattern. More...

class	ClampImageFilter
	Casts input pixels to output pixel type and clamps the output pixel values to a specified range. More...

class	ClosingByReconstructionImageFilter
	Closing by reconstruction of an image. More...

class	CollidingFrontsImageFilter
	Selects a region of space where two independent fronts run towards each other. More...

class	Command
	An implementation of the Command design pattern for callback. More...

class	ComplexToImaginaryImageFilter
	Computes pixel-wise the imaginary part of a complex image. More...

class	ComplexToModulusImageFilter
	Computes pixel-wise the Modulus of a complex image. More...

class	ComplexToPhaseImageFilter
	Computes pixel-wise the modulus of a complex image. More...

class	ComplexToRealImageFilter
	Computes pixel-wise the real(x) part of a complex image. More...

class	ComposeImageFilter
	ComposeImageFilter combine several scalar images into a multicomponent image. More...

class	CompositeTransform
	This class contains a stack of transforms and concatenates them by composition. More...

struct	ConditionalValue

class	ConfidenceConnectedImageFilter
	Segment pixels with similar statistics using connectivity. More...

class	ConnectedComponentImageFilter
	Label the objects in a binary image. More...

class	ConnectedThresholdImageFilter
	Label pixels that are connected to a seed and lie within a range of values. More...

class	ConstantPadImageFilter
	Increase the image size by padding with a constant value. More...

class	ConvolutionImageFilter
	Convolve a given image with an arbitrary image kernel. More...

class	CosImageFilter
	Computes the cosine of each pixel. More...

class	CropImageFilter
	Decrease the image size by cropping the image by an itk::Size at both the upper and lower bounds of the largest possible region. More...

class	CurvatureAnisotropicDiffusionImageFilter

class	CurvatureFlowImageFilter
	Denoise an image using curvature driven flow. More...

class	CyclicShiftImageFilter
	Perform a cyclic spatial shift of image intensities on the image grid. More...

class	DanielssonDistanceMapImageFilter
	This filter computes the distance map of the input image as an approximation with pixel accuracy to the Euclidean distance. More...

class	DemonsRegistrationFilter
	Deformably register two images using the demons algorithm. More...

class	DerivativeImageFilter
	Computes the directional derivative of an image. The directional derivative at each pixel location is computed by convolution with a derivative operator of user-specified order. More...

class	DICOMOrientImageFilter
	Permute axes and flip images as needed to obtain an approximation to the desired orientation. More...

class	DiffeomorphicDemonsRegistrationFilter
	Deformably register two images using a diffeomorphic demons algorithm. More...

class	DilateObjectMorphologyImageFilter
	dilation of an object in an image More...

class	DiscreteGaussianDerivativeImageFilter
	Calculates image derivatives using discrete derivative gaussian kernels. This filter calculates Gaussian derivative by separable convolution of an image and a discrete Gaussian derivative operator (kernel). More...

class	DiscreteGaussianImageFilter
	Blurs an image by separable convolution with discrete gaussian kernels. This filter performs Gaussian blurring by separable convolution of an image and a discrete Gaussian operator (kernel). More...

class	DisplacementFieldJacobianDeterminantFilter
	Computes a scalar image from a vector image (e.g., deformation field) input, where each output scalar at each pixel is the Jacobian determinant of the vector field at that location. This calculation is correct in the case where the vector image is a "displacement" from the current location. The computation for the jacobian determinant is: det[ dT/dx ] = det[ I + du/dx ]. More...

class	DisplacementFieldTransform
	A dense deformable transform over a bounded spatial domain for 2D or 3D coordinates space. More...

class	DivideFloorImageFilter
	Implements pixel-wise generic operation of two images, or of an image and a constant. More...

class	DivideImageFilter
	Pixel-wise division of two images. More...

class	DivideRealImageFilter
	Implements pixel-wise generic operation of two images, or of an image and a constant. More...

class	DoubleThresholdImageFilter
	Binarize an input image using double thresholding. More...

class	EdgePotentialImageFilter
	Computes the edge potential of an image from the image gradient. More...

class	EqualImageFilter
	Implements pixel-wise generic operation of two images, or of an image and a constant. More...

class	ErodeObjectMorphologyImageFilter
	Erosion of an object in an image. More...

class	Euler2DTransform
	A rigid 2D transform with rotation in radians around a fixed center with translation. More...

class	Euler3DTransform
	A rigid 3D transform with rotation in radians around a fixed center with translation. More...

class	ExpandImageFilter
	Expand the size of an image by an integer factor in each dimension. More...

class	ExpImageFilter
	Computes the exponential function of each pixel. More...

class	ExpNegativeImageFilter
	Computes the function exp(-K.x) for each input pixel. More...

class	ExtractImageFilter
	Decrease the image size by cropping the image to the selected region bounds. More...

class	FastApproximateRankImageFilter
	A separable rank filter. More...

class	FastMarchingBaseImageFilter
	Apply the Fast Marching method to solve an Eikonal equation on an image. More...

class	FastMarchingImageFilter
	Solve an Eikonal equation using Fast Marching. More...

class	FastMarchingUpwindGradientImageFilter
	Generates the upwind gradient field of fast marching arrival times. More...

class	FastSymmetricForcesDemonsRegistrationFilter
	Deformably register two images using a symmetric forces demons algorithm. More...

class	FFTConvolutionImageFilter
	Convolve a given image with an arbitrary image kernel using multiplication in the Fourier domain. More...

class	FFTNormalizedCorrelationImageFilter
	Calculate normalized cross correlation using FFTs. More...

class	FFTPadImageFilter
	Pad an image to make it suitable for an FFT transformation. More...

class	FFTShiftImageFilter
	Shift the zero-frequency components of a Fourier transform to the center of the image. More...

class	FlipImageFilter
	Flips an image across user specified axes. More...

class	ForwardFFTImageFilter
	Base class for forward Fast Fourier Transform . More...

class	FunctionCommand
	A Command class which allows setting an external function, or member function. More...

class	GaborImageSource
	Generate an n-dimensional image of a Gabor filter. More...

class	GaussianImageSource
	Generate an n-dimensional image of a Gaussian. More...

class	GenericException
	The base SimpleITK exception class. More...

class	GeodesicActiveContourLevelSetImageFilter
	Segments structures in images based on a user supplied edge potential map. More...

class	GradientAnisotropicDiffusionImageFilter

class	GradientImageFilter
	Computes the gradient of an image using directional derivatives. More...

class	GradientMagnitudeImageFilter
	Computes the gradient magnitude of an image region at each pixel. More...

class	GradientMagnitudeRecursiveGaussianImageFilter
	Computes the Magnitude of the Gradient of an image by convolution with the first derivative of a Gaussian. More...

class	GradientRecursiveGaussianImageFilter
	Computes the gradient of an image by convolution with the first derivative of a Gaussian. More...

class	GrayscaleConnectedClosingImageFilter
	Enhance pixels associated with a dark object (identified by a seed pixel) where the dark object is surrounded by a brighter object. More...

class	GrayscaleConnectedOpeningImageFilter
	Enhance pixels associated with a bright object (identified by a seed pixel) where the bright object is surrounded by a darker object. More...

class	GrayscaleDilateImageFilter
	Grayscale dilation of an image. More...

class	GrayscaleErodeImageFilter
	Grayscale erosion of an image. More...

class	GrayscaleFillholeImageFilter
	Remove local minima not connected to the boundary of the image. More...

class	GrayscaleGeodesicDilateImageFilter
	geodesic gray scale dilation of an image More...

class	GrayscaleGeodesicErodeImageFilter
	geodesic gray scale erosion of an image More...

class	GrayscaleGrindPeakImageFilter
	Remove local maxima not connected to the boundary of the image. More...

class	GrayscaleMorphologicalClosingImageFilter
	gray scale dilation of an image More...

class	GrayscaleMorphologicalOpeningImageFilter
	gray scale dilation of an image More...

class	GreaterEqualImageFilter
	Implements pixel-wise generic operation of two images, or of an image and a constant. More...

class	GreaterImageFilter
	Implements pixel-wise generic operation of two images, or of an image and a constant. More...

class	GridImageSource
	Generate an n-dimensional image of a grid. More...

class	HalfHermitianToRealInverseFFTImageFilter
	Base class for specialized complex-to-real inverse Fast Fourier Transform . More...

class	HashImageFilter
	Compute the sha1 or md5 hash of an image. More...

class	HausdorffDistanceImageFilter
	Computes the Hausdorff distance between the set of non-zero pixels of two images. More...

class	HConcaveImageFilter
	Identify local minima whose depth below the baseline is greater than h. More...

class	HConvexImageFilter
	Identify local maxima whose height above the baseline is greater than h. More...

class	HistogramMatchingImageFilter
	Normalize the grayscale values for a source image by matching the shape of the source image histogram to a reference histogram. More...

class	HMaximaImageFilter
	Suppress local maxima whose height above the baseline is less than h. More...

class	HMinimaImageFilter
	Suppress local minima whose depth below the baseline is less than h. More...

class	HuangThresholdImageFilter
	Threshold an image using the Huang Threshold. More...

class	Image
	The Image class for SimpleITK. More...

class	ImageFileReader
	Read an image file and return a SimpleITK Image. More...

class	ImageFileWriter
	Write out a SimpleITK image to the specified file location. More...

class	ImageFilter
	The base interface for SimpleITK filters that take one input image. More...

class	ImageReaderBase
	An abract base class for image readers. More...

class	ImageRegistrationMethod
	An interface method to the modular ITKv4 registration framework. More...

class	ImageSeriesReader
	Read series of image files into a SimpleITK image. More...

class	ImageSeriesWriter
	Writer series of image from a SimpleITK image. More...

struct	ImageTypeToPixelID

struct	ImageTypeToPixelID< itk::Image< TPixelType, VImageDimension > >

struct	ImageTypeToPixelID< itk::LabelMap< itk::LabelObject< TLabelType, VImageDimension > > >

struct	ImageTypeToPixelID< itk::VectorImage< TPixelType, VImageDimension > >

struct	ImageTypeToPixelIDValue

struct	ImageTypeToPixelIDValue< itk::ImageBase< VImageDimension > >

class	ImageViewer
	Display an image in an external viewer (Fiji by default) More...

class	ImportImageFilter
	Compose a 2D or 3D image and return a smart pointer to a SimpleITK image. More...

class	IntensityWindowingImageFilter
	Applies a linear transformation to the intensity levels of the input Image that are inside a user-defined interval. Values below this interval are mapped to a constant. Values over the interval are mapped to another constant. More...

class	IntermodesThresholdImageFilter
	Threshold an image using the Intermodes Threshold. More...

class	InverseDeconvolutionImageFilter
	The direct linear inverse deconvolution filter. More...

class	InverseDisplacementFieldImageFilter
	Computes the inverse of a displacement field. More...

class	InverseFFTImageFilter
	Base class for inverse Fast Fourier Transform . More...

class	InvertDisplacementFieldImageFilter
	Iteratively estimate the inverse field of a displacement field. More...

class	InvertIntensityImageFilter
	Invert the intensity of an image. More...

struct	IsBasic

struct	IsBasic< BasicPixelID< TPixelType > >

struct	IsBasic< itk::Image< TPixelType, VImageDimension > >

struct	IsInstantiated

struct	IsInstantiated< itk::Image< TPixelType, VImageDimension >, 0 >

struct	IsInstantiated< itk::LabelMap< itk::LabelObject< TLabelType, VImageDimension > >, 0 >

struct	IsInstantiated< itk::VectorImage< TPixelType, VImageDimension >, 0 >

struct	IsLabel

struct	IsLabel< itk::LabelMap< itk::LabelObject< TLabelType, VImageDimension > > >

struct	IsLabel< LabelPixelID< TPixelType > >

class	IsoContourDistanceImageFilter
	Compute an approximate distance from an interpolated isocontour to the close grid points. More...

class	IsoDataThresholdImageFilter
	Threshold an image using the IsoData Threshold. More...

class	IsolatedConnectedImageFilter
	Label pixels that are connected to one set of seeds but not another. More...

class	IsolatedWatershedImageFilter
	Isolate watershed basins using two seeds. More...

struct	IsVector

struct	IsVector< itk::VectorImage< TPixelType, VImageDimension > >

struct	IsVector< VectorPixelID< TPixelType > >

class	IterativeInverseDisplacementFieldImageFilter
	Computes the inverse of a displacement field. More...

class	JoinSeriesImageFilter
	Join N-D images into an (N+1)-D image. More...

class	KittlerIllingworthThresholdImageFilter
	Threshold an image using the KittlerIllingworth Threshold. More...

class	LabelContourImageFilter
	Labels the pixels on the border of the objects in a labeled image. More...

class	LabelImageToLabelMapFilter
	convert a labeled image to a label collection image More...

class	LabelIntensityStatisticsImageFilter
	a convenient class to convert a label image to a label map and valuate the statistics attributes at once More...

class	LabelMapContourOverlayImageFilter
	Apply a colormap to the contours (outlines) of each object in a label map and superimpose it on top of the feature image. More...

class	LabelMapMaskImageFilter
	Mask and image with a LabelMap . More...

class	LabelMapOverlayImageFilter
	Apply a colormap to a label map and superimpose it on an image. More...

class	LabelMapToBinaryImageFilter
	Convert a LabelMap to a binary image. More...

class	LabelMapToLabelImageFilter
	Converts a LabelMap to a labeled image. More...

class	LabelMapToRGBImageFilter
	Convert a LabelMap to a colored image. More...

class	LabelOverlapMeasuresImageFilter
	Computes overlap measures between the set same set of labels of pixels of two images. Background is assumed to be 0. More...

class	LabelOverlayImageFilter
	Apply a colormap to a label image and put it on top of the input image. More...

struct	LabelPixelID

class	LabelShapeStatisticsImageFilter
	Converts a label image to a label map and valuates the shape attributes. More...

class	LabelStatisticsImageFilter
	Given an intensity image and a label map, compute min, max, variance and mean of the pixels associated with each label or segment. More...

class	LabelToRGBImageFilter
	Apply a colormap to a label image. More...

class	LabelUniqueLabelMapFilter
	Make sure that the objects are not overlapping. More...

class	LabelVotingImageFilter
	This filter performs pixelwise voting among an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image). More...

class	LandmarkBasedTransformInitializerFilter

class	LandweberDeconvolutionImageFilter
	Deconvolve an image using the Landweber deconvolution algorithm. More...

class	LaplacianImageFilter

class	LaplacianRecursiveGaussianImageFilter
	Computes the Laplacian of Gaussian (LoG) of an image. More...

class	LaplacianSegmentationLevelSetImageFilter
	Segments structures in images based on a second derivative image features. More...

class	LaplacianSharpeningImageFilter
	This filter sharpens an image using a Laplacian. LaplacianSharpening highlights regions of rapid intensity change and therefore highlights or enhances the edges. The result is an image that appears more in focus. More...

class	LessEqualImageFilter
	Implements pixel-wise generic operation of two images, or of an image and a constant. More...

class	LessImageFilter
	Implements pixel-wise generic operation of two images, or of an image and a constant. More...

class	LevelSetMotionRegistrationFilter
	Deformably register two images using level set motion. More...

class	LiThresholdImageFilter
	Threshold an image using the Li Threshold. More...

class	Log10ImageFilter
	Computes the log10 of each pixel. More...

class	LogImageFilter
	Computes the log() of each pixel. More...

class	MagnitudeAndPhaseToComplexImageFilter
	Implements pixel-wise conversion of magnitude and phase data into complex voxels. More...

class	MaskedFFTNormalizedCorrelationImageFilter
	Calculate masked normalized cross correlation using FFTs. More...

class	MaskImageFilter
	Mask an image with a mask. More...

class	MaskNegatedImageFilter
	Mask an image with the negation (or logical compliment) of a mask. More...

class	MaximumEntropyThresholdImageFilter
	Threshold an image using the MaximumEntropy Threshold. More...

class	MaximumImageFilter
	Implements a pixel-wise operator Max(a,b) between two images. More...

class	MaximumProjectionImageFilter
	Maximum projection. More...

class	MeanImageFilter
	Applies an averaging filter to an image. More...

class	MeanProjectionImageFilter
	Mean projection. More...

class	MedianImageFilter
	Applies a median filter to an image. More...

class	MedianProjectionImageFilter
	Median projection. More...

class	MergeLabelMapFilter
	Merges several Label Maps. More...

class	MinimumImageFilter
	Implements a pixel-wise operator Min(a,b) between two images. More...

class	MinimumMaximumImageFilter
	Computes the minimum and the maximum intensity values of an image. More...

class	MinimumProjectionImageFilter
	Minimum projection. More...

class	MinMaxCurvatureFlowImageFilter
	Denoise an image using min/max curvature flow. More...

class	MirrorPadImageFilter
	Increase the image size by padding with replicants of the input image value. More...

class	ModulusImageFilter
	Computes the modulus (x % dividend) pixel-wise. More...

class	MomentsThresholdImageFilter
	Threshold an image using the Moments Threshold. More...

class	MorphologicalGradientImageFilter
	gray scale dilation of an image More...

class	MorphologicalWatershedFromMarkersImageFilter
	Morphological watershed transform from markers. More...

class	MorphologicalWatershedImageFilter
	Watershed segmentation implementation with morphological operators. More...

class	MultiLabelSTAPLEImageFilter
	This filter performs a pixelwise combination of an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image). More...

class	MultiplyImageFilter
	Pixel-wise multiplication of two images. More...

class	N4BiasFieldCorrectionImageFilter
	Implementation of the N4 bias field correction algorithm. More...

class	NaryAddImageFilter
	Pixel-wise addition of N images. More...

class	NaryMaximumImageFilter
	Computes the pixel-wise maximum of several images. More...

class	NeighborhoodConnectedImageFilter
	Label pixels that are connected to a seed and lie within a neighborhood. More...

class	NoiseImageFilter
	Calculate the local noise in an image. More...

class	NonCopyable
	An inheritable class to disable copying of a class. More...

class	NormalizedCorrelationImageFilter
	Computes the normalized correlation of an image and a template. More...

class	NormalizeImageFilter
	Normalize an image by setting its mean to zero and variance to one. More...

class	NormalizeToConstantImageFilter
	Scales image pixel intensities to make the sum of all pixels equal a user-defined constant. More...

class	NotEqualImageFilter
	Implements pixel-wise generic operation of two images, or of an image and a constant. More...

class	NotImageFilter
	Implements the NOT logical operator pixel-wise on an image. More...

class	ObjectnessMeasureImageFilter
	Enhance M-dimensional objects in N-dimensional images. More...

class	OpeningByReconstructionImageFilter
	Opening by reconstruction of an image. More...

class	OrImageFilter
	Implements the OR bitwise operator pixel-wise between two images. More...

class	OtsuMultipleThresholdsImageFilter
	Threshold an image using multiple Otsu Thresholds. More...

class	OtsuThresholdImageFilter
	Threshold an image using the Otsu Threshold. More...

class	PasteImageFilter
	Paste an image (or a constant value) into another image. More...

class	PatchBasedDenoisingImageFilter
	Derived class implementing a specific patch-based denoising algorithm, as detailed below. More...

class	PermuteAxesImageFilter
	Permutes the image axes according to a user specified order. More...

class	PhysicalPointImageSource
	Generate an image of the physical locations of each pixel. More...

class	PimpleImageBase
	Private implementation idiom image base class. More...

struct	PixelIDToImageType

struct	PixelIDToImageType< BasicPixelID< TPixelType >, VImageDimension >

struct	PixelIDToImageType< LabelPixelID< TLabelType >, VImageDimension >

struct	PixelIDToImageType< VectorPixelID< TVectorPixelType >, VImageDimension >

struct	PixelIDToPixelIDValue

class	PowImageFilter
	Computes the powers of 2 images. More...

class	ProcessObject
	Base class for SimpleITK classes based on ProcessObject. More...

class	ProjectedLandweberDeconvolutionImageFilter
	Deconvolve an image using the projected Landweber deconvolution algorithm. More...

class	RankImageFilter
	Rank filter of a greyscale image. More...

class	RealAndImaginaryToComplexImageFilter
	ComposeImageFilter combine several scalar images into a multicomponent image. More...

class	RealToHalfHermitianForwardFFTImageFilter
	Base class for specialized real-to-complex forward Fast Fourier Transform . More...

class	ReconstructionByDilationImageFilter
	grayscale reconstruction by dilation of an image More...

class	ReconstructionByErosionImageFilter
	grayscale reconstruction by erosion of an image More...

class	RecursiveGaussianImageFilter
	Base class for computing IIR convolution with an approximation of a Gaussian kernel. More...

class	RegionalMaximaImageFilter
	Produce a binary image where foreground is the regional maxima of the input image. More...

class	RegionalMinimaImageFilter
	Produce a binary image where foreground is the regional minima of the input image. More...

class	RegionOfInterestImageFilter
	Extract a region of interest from the input image. More...

class	RelabelComponentImageFilter
	Relabel the components in an image such that consecutive labels are used. More...

class	RelabelLabelMapFilter
	This filter relabels the LabelObjects; the new labels are arranged consecutively with consideration for the background value. More...

class	RenyiEntropyThresholdImageFilter
	Threshold an image using the RenyiEntropy Threshold. More...

class	ResampleImageFilter
	Resample an image via a coordinate transform. More...

class	RescaleIntensityImageFilter
	Applies a linear transformation to the intensity levels of the input Image . More...

class	RichardsonLucyDeconvolutionImageFilter
	Deconvolve an image using the Richardson-Lucy deconvolution algorithm. More...

class	RoundImageFilter
	Rounds the value of each pixel. More...

class	SaltAndPepperNoiseImageFilter
	Alter an image with fixed value impulse noise, often called salt and pepper noise. More...

class	ScalarChanAndVeseDenseLevelSetImageFilter
	Dense implementation of the Chan and Vese multiphase level set image filter. More...

class	ScalarConnectedComponentImageFilter
	A connected components filter that labels the objects in an arbitrary image. Two pixels are similar if they are within threshold of each other. Uses ConnectedComponentFunctorImageFilter . More...

class	ScalarImageKmeansImageFilter
	Classifies the intensity values of a scalar image using the K-Means algorithm. More...

class	ScalarToRGBColormapImageFilter
	Implements pixel-wise intensity->rgb mapping operation on one image. More...

class	ScaleSkewVersor3DTransform
	A over parameterized 3D Affine transform composed of the addition of a versor rotation matrix, a scale matrix and a skew matrix around a fixed center with translation. More...

class	ScaleTransform
	A 2D or 3D anisotropic scale of coordinate space around a fixed center. More...

class	ScaleVersor3DTransform
	A parameterized 3D transform composed of the addition of a versor rotation matrix and a scale matrix around a fixed center with translation. More...

struct	scope_exit

class	ShanbhagThresholdImageFilter
	Threshold an image using the Shanbhag Threshold. More...

class	ShapeDetectionLevelSetImageFilter
	Segments structures in images based on a user supplied edge potential map. More...

class	ShiftScaleImageFilter
	Shift and scale the pixels in an image. More...

class	ShotNoiseImageFilter
	Alter an image with shot noise. More...

class	ShrinkImageFilter
	Reduce the size of an image by an integer factor in each dimension. More...

class	SigmoidImageFilter
	Computes the sigmoid function pixel-wise. More...

class	SignedDanielssonDistanceMapImageFilter

class	SignedMaurerDistanceMapImageFilter
	This filter calculates the Euclidean distance transform of a binary image in linear time for arbitrary dimensions. More...

class	Similarity2DTransform
	A similarity 2D transform with rotation in radians and isotropic scaling around a fixed center with translation. More...

class	Similarity3DTransform
	A similarity 3D transform with rotation as a versor, and isotropic scaling around a fixed center with translation. More...

class	SimilarityIndexImageFilter
	Measures the similarity between the set of non-zero pixels of two images. More...

class	SimpleContourExtractorImageFilter
	Computes an image of contours which will be the contour of the first image. More...

class	SinImageFilter
	Computes the sine of each pixel. More...

class	SliceImageFilter
	Slices an image based on a starting index and a stopping index, and a step size. More...

class	SLICImageFilter
	Simple Linear Iterative Clustering (SLIC) super-pixel segmentation. More...

class	SmoothingRecursiveGaussianImageFilter
	Computes the smoothing of an image by convolution with the Gaussian kernels implemented as IIR filters. More...

class	SobelEdgeDetectionImageFilter
	A 2D or 3D edge detection using the Sobel operator. More...

class	SpeckleNoiseImageFilter
	Alter an image with speckle (multiplicative) noise. More...

class	SqrtImageFilter
	Computes the square root of each pixel. More...

class	SquaredDifferenceImageFilter
	Implements pixel-wise the computation of squared difference. More...

class	SquareImageFilter
	Computes the square of the intensity values pixel-wise. More...

class	StandardDeviationProjectionImageFilter
	Mean projection. More...

class	STAPLEImageFilter
	The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations. More...

class	StatisticsImageFilter
	Compute min, max, variance and mean of an Image . More...

class	StochasticFractalDimensionImageFilter
	This filter computes the stochastic fractal dimension of the input image. More...

class	SubtractImageFilter
	Pixel-wise subtraction of two images. More...

class	SumProjectionImageFilter
	Sum projection. More...

class	SymmetricForcesDemonsRegistrationFilter
	Deformably register two images using the demons algorithm. More...

class	TanImageFilter
	Computes the tangent of each input pixel. More...

class	TernaryAddImageFilter
	Pixel-wise addition of three images. More...

class	TernaryMagnitudeImageFilter
	Compute the pixel-wise magnitude of three images. More...

class	TernaryMagnitudeSquaredImageFilter
	Compute the pixel-wise squared magnitude of three images. More...

class	ThresholdImageFilter
	Set image values to a user-specified value if they are below, above, or between simple threshold values. More...

class	ThresholdMaximumConnectedComponentsImageFilter
	Finds the threshold value of an image based on maximizing the number of objects in the image that are larger than a given minimal size. More...

class	ThresholdSegmentationLevelSetImageFilter
	Segments structures in images based on intensity values. More...

class	TikhonovDeconvolutionImageFilter
	An inverse deconvolution filter regularized in the Tikhonov sense. More...

class	TileImageFilter
	Tile multiple input images into a single output image. More...

class	TobogganImageFilter
	toboggan image segmentation The Toboggan segmentation takes a gradient magnitude image as input and produces an (over-)segmentation of the image based on connecting each pixel to a local minimum of gradient. It is roughly equivalent to a watershed segmentation of the lowest level. More...

class	Transform
	A simplified wrapper around a variety of ITK transforms. More...

class	TransformToDisplacementFieldFilter
	Generate a displacement field from a coordinate transform. More...

class	TranslationTransform
	Translation of a 2D or 3D coordinate space. More...

class	TriangleThresholdImageFilter
	Threshold an image using the Triangle Threshold. More...

class	UnaryMinusImageFilter
	Implements pixel-wise generic operation on one image. More...

class	UnsharpMaskImageFilter
	Edge enhancement filter. More...

class	ValuedRegionalMaximaImageFilter
	Transforms the image so that any pixel that is not a regional maxima is set to the minimum value for the pixel type. Pixels that are regional maxima retain their value. More...

class	ValuedRegionalMinimaImageFilter
	Transforms the image so that any pixel that is not a regional minima is set to the maximum value for the pixel type. Pixels that are regional minima retain their value. More...

class	VectorConfidenceConnectedImageFilter
	Segment pixels with similar statistics using connectivity. More...

class	VectorConnectedComponentImageFilter
	A connected components filter that labels the objects in a vector image. Two vectors are pointing similar directions if one minus their dot product is less than a threshold. Vectors that are 180 degrees out of phase are similar. Assumes that vectors are normalized. More...

class	VectorIndexSelectionCastImageFilter
	Extracts the selected index of the vector that is the input pixel type. More...

class	VectorMagnitudeImageFilter
	Take an image of vectors as input and produce an image with the magnitude of those vectors. More...

struct	VectorPixelID

class	Version
	Version info for SimpleITK. More...

class	VersorRigid3DTransform
	A rotation as a versor around a fixed center with translation of a 3D coordinate space. More...

class	VersorTransform
	A 3D rotation transform with rotation as a versor around a fixed center. More...

class	VotingBinaryHoleFillingImageFilter
	Fills in holes and cavities by applying a voting operation on each pixel. More...

class	VotingBinaryImageFilter
	Applies a voting operation in a neighborhood of each pixel. More...

class	VotingBinaryIterativeHoleFillingImageFilter
	Fills in holes and cavities by iteratively applying a voting operation. More...

class	WarpImageFilter
	Warps an image using an input displacement field. More...

class	WhiteTopHatImageFilter
	White top hat extracts local maxima that are larger than the structuring element. More...

class	WienerDeconvolutionImageFilter
	The Wiener deconvolution image filter is designed to restore an image convolved with a blurring kernel while keeping noise enhancement to a minimum. More...

class	WrapPadImageFilter
	Increase the image size by padding with replicants of the input image value. More...

class	XorImageFilter
	Computes the XOR bitwise operator pixel-wise between two images. More...

class	YenThresholdImageFilter
	Threshold an image using the Yen Threshold. More...

class	ZeroCrossingBasedEdgeDetectionImageFilter
	This filter implements a zero-crossing based edge detecor. More...

class	ZeroCrossingImageFilter
	This filter finds the closest pixel to the zero-crossings (sign changes) in a signed itk::Image . More...

class	ZeroFluxNeumannPadImageFilter
	Increase the image size by padding according to the zero-flux Neumann boundary condition. More...

Typedefs
typedef typelist::Append< typelist::Append< BasicPixelIDTypeList, ComplexPixelIDTypeList >::Type, typelist::Append< VectorPixelIDTypeList, LabelPixelIDTypeList >::Type >::Type	AllPixelIDTypeList

typedef typelist::MakeTypeList< BasicPixelID< int8_t >, BasicPixelID< uint8_t >, BasicPixelID< int16_t >, BasicPixelID< uint16_t >, BasicPixelID< int32_t >, BasicPixelID< uint32_t >, BasicPixelID< float >, BasicPixelID< double > >::Type	BasicPixelIDTypeList

typedef typelist::MakeTypeList< BasicPixelID< std::complex< float > >, BasicPixelID< std::complex< double > > >::Type	ComplexPixelIDTypeList

using	FalseType = std::false_type

using	InstantiatedPixelIDTypeList = AllPixelIDTypeList

using	IntegerLabelPixelIDTypeList = UnsignedIntegerPixelIDTypeList

typedef typelist::MakeTypeList< BasicPixelID< int8_t >, BasicPixelID< uint8_t >, BasicPixelID< int16_t >, BasicPixelID< uint16_t >, BasicPixelID< int32_t >, BasicPixelID< uint32_t > >::Type	IntegerPixelIDTypeList

typedef typelist::MakeTypeList< LabelPixelID< uint8_t >, LabelPixelID< uint16_t >, LabelPixelID< uint32_t > >::Type	LabelPixelIDTypeList

typedef typelist::Append< typelist::Append< BasicPixelIDTypeList, ComplexPixelIDTypeList >::Type, VectorPixelIDTypeList >::Type	NonLabelPixelIDTypeList

using	PixelIDValueType = int

typedef typelist::MakeTypeList< BasicPixelID< float >, BasicPixelID< double > >::Type	RealPixelIDTypeList

typedef typelist::MakeTypeList< VectorPixelID< float >, VectorPixelID< double > >::Type	RealVectorPixelIDTypeList

using	ScalarPixelIDTypeList = BasicPixelIDTypeList

typedef typelist::MakeTypeList< BasicPixelID< int8_t >, BasicPixelID< int16_t >, BasicPixelID< int32_t >, BasicPixelID< float >, BasicPixelID< double > >::Type	SignedPixelIDTypeList

typedef typelist::MakeTypeList< VectorPixelID< int8_t >, VectorPixelID< int16_t >, VectorPixelID< int32_t >, VectorPixelID< float >, VectorPixelID< double > >::Type	SignedVectorPixelIDTypeList

using	TrueType = std::true_type

typedef typelist::MakeTypeList< BasicPixelID< uint8_t >, BasicPixelID< uint16_t >, BasicPixelID< uint32_t > >::Type	UnsignedIntegerPixelIDTypeList

typedef typelist::MakeTypeList< VectorPixelID< int8_t >, VectorPixelID< uint8_t >, VectorPixelID< int16_t >, VectorPixelID< uint16_t >, VectorPixelID< int32_t >, VectorPixelID< uint32_t >, VectorPixelID< float >, VectorPixelID< double > >::Type	VectorPixelIDTypeList

Enumerations
enum	EventEnum { sitkAnyEvent = 0, sitkAbortEvent = 1, sitkDeleteEvent = 2, sitkEndEvent = 3, sitkIterationEvent = 4, sitkProgressEvent = 5, sitkStartEvent = 6, sitkMultiResolutionIterationEvent = 9, sitkUserEvent = 7 }
	Events which can be observed from ProcessObject. More...

enum	InterpolatorEnum { sitkNearestNeighbor = 1, sitkLinear = 2, sitkBSpline = 3, sitkGaussian = 4, sitkLabelGaussian = 5, sitkHammingWindowedSinc = 6, sitkCosineWindowedSinc = 7, sitkWelchWindowedSinc = 8, sitkLanczosWindowedSinc = 9, sitkBlackmanWindowedSinc = 10, sitkBSplineResampler = 11, sitkBSplineResamplerOrder3 = 11, sitkBSplineResamplerOrder1 = 12, sitkBSplineResamplerOrder2 = 13, sitkBSplineResamplerOrder4 = 14, sitkBSplineResamplerOrder5 = 15 }

enum	KernelEnum { sitkAnnulus, sitkBall, sitkBox, sitkCross, sitkPolygon3, sitkPolygon4, sitkPolygon5, sitkPolygon6, sitkPolygon7, sitkPolygon8, sitkPolygon9 }

enum	PixelIDValueEnum { sitkUnknown = -1, sitkUInt8 = PixelIDToPixelIDValue< BasicPixelID<uint8_t> >::Result, sitkInt8 = PixelIDToPixelIDValue< BasicPixelID<int8_t> >::Result, sitkUInt16 = PixelIDToPixelIDValue< BasicPixelID<uint16_t> >::Result, sitkInt16 = PixelIDToPixelIDValue< BasicPixelID<int16_t> >::Result, sitkUInt32 = PixelIDToPixelIDValue< BasicPixelID<uint32_t> >::Result, sitkInt32 = PixelIDToPixelIDValue< BasicPixelID<int32_t> >::Result, sitkUInt64 = PixelIDToPixelIDValue< BasicPixelID<uint64_t> >::Result, sitkInt64 = PixelIDToPixelIDValue< BasicPixelID<int64_t> >::Result, sitkFloat32 = PixelIDToPixelIDValue< BasicPixelID<float> >::Result, sitkFloat64 = PixelIDToPixelIDValue< BasicPixelID<double> >::Result, sitkComplexFloat32 = PixelIDToPixelIDValue< BasicPixelID<std::complex<float> > >::Result, sitkComplexFloat64 = PixelIDToPixelIDValue< BasicPixelID<std::complex<double> > >::Result, sitkVectorUInt8 = PixelIDToPixelIDValue< VectorPixelID<uint8_t> >::Result, sitkVectorInt8 = PixelIDToPixelIDValue< VectorPixelID<int8_t> >::Result, sitkVectorUInt16 = PixelIDToPixelIDValue< VectorPixelID<uint16_t> >::Result, sitkVectorInt16 = PixelIDToPixelIDValue< VectorPixelID<int16_t> >::Result, sitkVectorUInt32 = PixelIDToPixelIDValue< VectorPixelID<uint32_t> >::Result, sitkVectorInt32 = PixelIDToPixelIDValue< VectorPixelID<int32_t> >::Result, sitkVectorUInt64 = PixelIDToPixelIDValue< VectorPixelID<uint64_t> >::Result, sitkVectorInt64 = PixelIDToPixelIDValue< VectorPixelID<int64_t> >::Result, sitkVectorFloat32 = PixelIDToPixelIDValue< VectorPixelID<float> >::Result, sitkVectorFloat64 = PixelIDToPixelIDValue< VectorPixelID<double> >::Result, sitkLabelUInt8 = PixelIDToPixelIDValue< LabelPixelID<uint8_t> >::Result, sitkLabelUInt16 = PixelIDToPixelIDValue< LabelPixelID<uint16_t> >::Result, sitkLabelUInt32 = PixelIDToPixelIDValue< LabelPixelID<uint32_t> >::Result, sitkLabelUInt64 = PixelIDToPixelIDValue< LabelPixelID<uint64_t> >::Result }
	Enumerated values of pixelIDs. More...

enum	SeedEnum { sitkWallClock = 0 }

enum	TransformEnum { sitkUnknownTransform = -1, sitkIdentity, sitkTranslation, sitkScale, sitkScaleLogarithmic, sitkEuler, sitkSimilarity, sitkQuaternionRigid, sitkVersor, sitkVersorRigid, sitkScaleSkewVersor, sitkScaleVersor, sitkAffine, sitkComposite, sitkDisplacementField, sitkBSplineTransform }

Functions
Image	AbsoluteValueDifference (const Image &image1, double constant)

Image	AbsoluteValueDifference (double constant, const Image &image2)

Image	AbsoluteValueDifference (Image &&image1, double constant)

Image	Add (const Image &image1, double constant)

Image	Add (double constant, const Image &image2)

Image	Add (Image &&image1, double constant)

Image	And (const Image &image1, int constant)

Image	And (Image &&image1, int constant)

Image	And (int constant, const Image &image2)

Image	Atan2 (const Image &image1, double constant)

Image	Atan2 (double constant, const Image &image2)

Image	Atan2 (Image &&image1, double constant)

BSplineTransform	BSplineTransformInitializer (const Image &image1, const std::vector< uint32_t > &transformDomainMeshSize=std::vector< uint32_t >(3, 1u), unsigned int order=3u)
	BSplineTransformInitializerFilter is a helper class intended to initialize the control point grid such that it has a physically consistent definition. It sets the transform domain origin, physical dimensions and direction from information obtained from the image. It also sets the mesh size if asked to do so by calling SetTransformDomainMeshSize()before calling InitializeTransform(). More...

Image	Cast (const Image &image, PixelIDValueEnum pixelID)

Transform	CenteredTransformInitializer (const Image &fixedImage, const Image &movingImage, const Transform &transform, CenteredTransformInitializerFilter::OperationModeType operationMode=itk::simple::CenteredTransformInitializerFilter::MOMENTS)
	CenteredTransformInitializer is a helper class intended to initialize the center of rotation and the translation of Transforms having the center of rotation among their parameters. More...

Transform	CenteredVersorTransformInitializer (const Image &fixedImage, const Image &movingImage, const Transform &transform, bool computeRotation=false)
	CenteredVersorTransformInitializer is a helper class intended to initialize the center of rotation, versor, and translation of the VersorRigid3DTransform. More...

template<unsigned int VImageDimension>
itk::FlatStructuringElement< VImageDimension >	CreateKernel (KernelEnum kernelType, const std::vector< uint32_t > &size)

Image	DiscreteGaussian (const Image &image1, double variance, unsigned int maximumKernelWidth=32u, double maximumError=0.01, bool useImageSpacing=true)
	Blurs an image by separable convolution with discrete gaussian kernels. This filter performs Gaussian blurring by separable convolution of an image and a discrete Gaussian operator (kernel). More...

Image	Divide (const Image &image1, double constant)

Image	Divide (double constant, const Image &image2)

Image	Divide (Image &&image1, double constant)

Image	DivideFloor (const Image &image1, double constant)

Image	DivideFloor (double constant, const Image &image2)

Image	DivideFloor (Image &&image1, double constant)

Image	DivideReal (const Image &image1, double constant)

Image	DivideReal (double constant, const Image &image2)

Image	DivideReal (Image &&image1, double constant)

Image	Equal (const Image &image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	Equal (double constant, const Image &image2, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	Equal (Image &&image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	GaborSource (PixelIDValueEnum outputPixelType=itk::simple::sitkFloat32, std::vector< unsigned int > size=std::vector< unsigned int >(3, 64), std::vector< double > sigma=std::vector< double >(3, 16.0), std::vector< double > mean=std::vector< double >(3, 32.0), double frequency=0.4, std::vector< double > origin=std::vector< double >(3, 0.0), std::vector< double > spacing=std::vector< double >(3, 1.0), std::vector< double > direction=std::vector< double >())
	Generate an n-dimensional image of a Gabor filter. More...

Image	GaussianSource (PixelIDValueEnum outputPixelType=itk::simple::sitkFloat32, std::vector< unsigned int > size=std::vector< unsigned int >(3, 64), std::vector< double > sigma=std::vector< double >(3, 16.0), std::vector< double > mean=std::vector< double >(3, 32.0), double scale=255, std::vector< double > origin=std::vector< double >(3, 0.0), std::vector< double > spacing=std::vector< double >(3, 1.0), std::vector< double > direction=std::vector< double >(), bool normalized=false)
	Generate an n-dimensional image of a Gaussian. More...

template<typename TPixelType , unsigned int ImageDimension>
SITKCommon_HIDDEN itk::Image< itk::Vector< TPixelType, ImageDimension >, ImageDimension >::Pointer	GetImageFromVectorImage (itk::VectorImage< TPixelType, ImageDimension > *img, bool transferOwnership=false)
	A utility method to help convert between itk image types efficiently. More...

const std::string SITKCommon_EXPORT	GetPixelIDValueAsString (PixelIDValueEnum type)

const std::string SITKCommon_EXPORT	GetPixelIDValueAsString (PixelIDValueType type)

PixelIDValueType SITKCommon_EXPORT	GetPixelIDValueFromString (const std::string &enumString)
	Function mapping enumeration names in std::string to values. More...

template<class TPixelType , unsigned int NImageDimension, unsigned int NLength>
SITKCommon_HIDDEN itk::VectorImage< TPixelType, NImageDimension >::Pointer	GetVectorImageFromImage (itk::Image< itk::CovariantVector< TPixelType, NLength >, NImageDimension > *img, bool transferOwnership=false)

template<class TPixelType , unsigned int NImageDimension, unsigned int NLength>
SITKCommon_HIDDEN itk::VectorImage< TPixelType, NImageDimension >::Pointer	GetVectorImageFromImage (itk::Image< itk::Vector< TPixelType, NLength >, NImageDimension > *img, bool transferOwnership=false)

Image	Greater (const Image &image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	Greater (double constant, const Image &image2, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	Greater (Image &&image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	GreaterEqual (const Image &image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	GreaterEqual (double constant, const Image &image2, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	GreaterEqual (Image &&image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	GridSource (PixelIDValueEnum outputPixelType=itk::simple::sitkFloat32, std::vector< unsigned int > size=std::vector< unsigned int >(3, 64), std::vector< double > sigma=std::vector< double >(3, 0.5), std::vector< double > gridSpacing=std::vector< double >(3, 4.0), std::vector< double > gridOffset=std::vector< double >(3, 0.0), double scale=255.0, std::vector< double > origin=std::vector< double >(3, 0.0), std::vector< double > spacing=std::vector< double >(3, 1.0), std::vector< double > direction=std::vector< double >())
	Generate an n-dimensional image of a grid. More...

std::string	Hash (const Image &image, HashImageFilter::HashFunction function=HashImageFilter::SHA1)

Image SITKIO_EXPORT	ImportAsDouble (double *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsFloat (float *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsInt16 (int16_t *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsInt32 (int32_t *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsInt64 (int64_t *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsInt8 (int8_t *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsUInt16 (uint16_t *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsUInt32 (uint32_t *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsUInt64 (uint64_t *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Image SITKIO_EXPORT	ImportAsUInt8 (uint8_t *buffer, const std::vector< unsigned int > &size, const std::vector< double > &spacing=std::vector< double >(3, 1.0), const std::vector< double > &origin=std::vector< double >(3, 0.0), const std::vector< double > &direction=std::vector< double >(), unsigned int numberOfComponents=1)

Transform	LandmarkBasedTransformInitializer (const Transform &transform, const std::vector< double > &fixedLandmarks=std::vector< double >(), const std::vector< double > &movingLandmarks=std::vector< double >(), const std::vector< double > &landmarkWeight=std::vector< double >(), const Image &referenceImage=Image(), unsigned int numberOfControlPoints=4u)
	itk::simple::LandmarkBasedTransformInitializerFilter Procedural Interface More...

Image	Less (const Image &image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	Less (double constant, const Image &image2, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	Less (Image &&image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	LessEqual (const Image &image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	LessEqual (double constant, const Image &image2, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	LessEqual (Image &&image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	MagnitudeAndPhaseToComplex (const Image &image1, double constant)

Image	MagnitudeAndPhaseToComplex (double constant, const Image &image2)

Image	MagnitudeAndPhaseToComplex (Image &&image1, double constant)

template<typename F >
scope_exit< F >	make_scope_exit (F &&f) noexcept

Image	Maximum (const Image &image1, double constant)

Image	Maximum (double constant, const Image &image2)

Image	Maximum (Image &&image1, double constant)

Image	Minimum (const Image &image1, double constant)

Image	Minimum (double constant, const Image &image2)

Image	Minimum (Image &&image1, double constant)

Image	Modulus (const Image &image1, uint32_t constant)

Image	Modulus (Image &&image1, uint32_t constant)

Image	Modulus (uint32_t constant, const Image &image2)

Image	Multiply (const Image &image1, double constant)

Image	Multiply (double constant, const Image &image2)

Image	Multiply (Image &&image1, double constant)

Image	NotEqual (const Image &image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	NotEqual (double constant, const Image &image2, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

Image	NotEqual (Image &&image1, double constant, uint8_t backgroundValue=0u, uint8_t foregroundValue=1u)

SITKCommon_EXPORT std::ostream &	operator<< (std::ostream &os, const EventEnum k)

SITKCommon_EXPORT std::ostream &	operator<< (std::ostream &os, const InterpolatorEnum i)

SITKCommon_EXPORT std::ostream &	operator<< (std::ostream &os, const KernelEnum k)

SITKCommon_EXPORT std::ostream &	operator<< (std::ostream &os, const PixelIDValueEnum id)

template<typename T >
SITKCommon_HIDDEN std::ostream &	operator<< (std::ostream &os, const std::vector< T > &v)
	Output the element of an std::vector to the output stream. More...

Image	Or (const Image &image1, int constant)

Image	Or (Image &&image1, int constant)

Image	Or (int constant, const Image &image2)

Image	PatchBasedDenoising (const Image &image1, double kernelBandwidthSigma=400.0, uint32_t patchRadius=4u, uint32_t numberOfIterations=1u, uint32_t numberOfSamplePatches=200u, double sampleVariance=400.0)

Image	PatchBasedDenoising (const Image &image1, itk::simple::PatchBasedDenoisingImageFilter::NoiseModelType noiseModel, double kernelBandwidthSigma=400.0, uint32_t patchRadius=4u, uint32_t numberOfIterations=1u, uint32_t numberOfSamplePatches=200u, double sampleVariance=400.0, double noiseSigma=0.0, double noiseModelFidelityWeight=0.0)
	itk::simple::PatchBasedDenoisingImageFilter Procedural Interface More...

Image	PhysicalPointSource (PixelIDValueEnum outputPixelType=itk::simple::sitkVectorFloat32, std::vector< unsigned int > size=std::vector< unsigned int >(3, 64), std::vector< double > origin=std::vector< double >(3, 0.0), std::vector< double > spacing=std::vector< double >(3, 1.0), std::vector< double > direction=std::vector< double >())
	Generate an image of the physical locations of each pixel. More...

Image	Pow (const Image &image1, double constant)

Image	Pow (double constant, const Image &image2)

Image	Pow (Image &&image1, double constant)

SITKIO_EXPORT Image	ReadImage (const std::string &filename, PixelIDValueEnum outputPixelType=sitkUnknown, const std::string &imageIO="")
	ReadImage is a procedural interface to the ImageFileReader class which is convenient for most image reading tasks. More...

SITKIO_EXPORT Image	ReadImage (const std::vector< std::string > &fileNames, PixelIDValueEnum outputPixelType=sitkUnknown, const std::string &imageIO="")
	ReadImage is a procedural interface to the ImageSeriesReader class which is convenient for most image reading tasks. More...

SITKCommon_EXPORT Transform	ReadTransform (const std::string &filename)

void SITKIO_EXPORT	Show (const Image &image, const std::string &title="", const bool debugOn=ProcessObject::GetGlobalDefaultDebug())

template<typename TDirectionType >
std::vector< double > SITKCommon_HIDDEN	sitkITKDirectionToSTL (const TDirectionType &d)

template<unsigned int VImageDimension>
std::vector< unsigned int > SITKCommon_HIDDEN	sitkITKImageRegionToSTL (const ImageRegion< VImageDimension > &in)
	Convert an ITK ImageRegion to and std::vector with the first part being the start index followed by the size. More...

template<typename TType , typename TITKVector >
std::vector< TType > SITKCommon_HIDDEN	sitkITKVectorToSTL (const std::vector< TITKVector > &in)

template<typename TType , typename TITKVector >
std::vector< TType > SITKCommon_HIDDEN	sitkITKVectorToSTL (const TITKVector &in)
	Convert an ITK fixed width vector to a std::vector. More...

template<typename TType , typename T >
std::vector< TType > SITKCommon_HIDDEN	sitkITKVersorToSTL (const itk::Versor< T > &in)

template<typename TDirectionType >
TDirectionType SITKCommon_HIDDEN	sitkSTLToITKDirection (const std::vector< double > &direction)

template<typename TITKVector , typename TType >
TITKVector SITKCommon_HIDDEN	sitkSTLVectorToITK (const std::vector< TType > &in)
	Copy the elements of an std::vector into an ITK fixed width vector. More...

template<typename TITKPointVector , typename TType >
TITKPointVector SITKCommon_HIDDEN	sitkSTLVectorToITKPointVector (const std::vector< TType > &in)

template<typename T , typename TType >
itk::Versor< T > SITKCommon_HIDDEN	sitkSTLVectorToITKVersor (const std::vector< TType > &in)

template<typename TType , typename TVectorOfITKVector >
std::vector< TType > SITKCommon_HIDDEN	sitkVectorOfITKVectorToSTL (const TVectorOfITKVector &in)
	Convert an ITK style array of ITK fixed witdth vector to std::vector. More...

Image	SmoothingRecursiveGaussian (const Image &image1, double sigma, bool normalizeAcrossScale=false)
	Computes the smoothing of an image by convolution with the Gaussian kernels implemented as IIR filters. More...

Image	SquaredDifference (const Image &image1, double constant)

Image	SquaredDifference (double constant, const Image &image2)

Image	SquaredDifference (Image &&image1, double constant)

Image	Subtract (const Image &image1, double constant)

Image	Subtract (double constant, const Image &image2)

Image	Subtract (Image &&image1, double constant)

Image	TransformToDisplacementField (const Transform &transform, PixelIDValueEnum outputPixelType=itk::simple::sitkVectorFloat64, std::vector< unsigned int > size=std::vector< unsigned int >(3, 64), std::vector< double > outputOrigin=std::vector< double >(3, 0.0), std::vector< double > outputSpacing=std::vector< double >(3, 1.0), std::vector< double > outputDirection=std::vector< double >())
	Generate a displacement field from a coordinate transform. More...

template<typename T >
void SITKCommon_HIDDEN	Unused (const T &)
	A function which does nothing. More...

SITKIO_EXPORT void	WriteImage (const Image &image, const std::string &fileName, bool useCompression=false, int compressionLevel=-1)
	WriteImage is a procedural interface to the ImageFileWriter. class which is convenient for many image writing tasks. More...

SITKIO_EXPORT void	WriteImage (const Image &image, const std::vector< std::string > &fileNames, bool useCompression=false, int compressionLevel=-1)
	WriteImage is a procedural interface to the ImageSeriesWriter. class which is convenient for many image writing tasks. More...

SITKCommon_EXPORT void	WriteTransform (const Transform &transform, const std::string &filename)

Image	Xor (const Image &image1, int constant)

Image	Xor (Image &&image1, int constant)

Image	Xor (int constant, const Image &image2)

Typedef Documentation

◆ AllPixelIDTypeList

typedef typelist::Append< typelist::Append< BasicPixelIDTypeList, ComplexPixelIDTypeList >::Type, typelist::Append< VectorPixelIDTypeList, LabelPixelIDTypeList >::Type >::Type itk::simple::AllPixelIDTypeList

List of all pixel ids available, this include image of itk::Image, itk::VectorImage, and itk::LabelMap types.

Todo:: This needs to be extended to include LabelMap pixel ids.

See also: BasicPixelID; VectorPixelID; LabelPixelID

Definition at line 195 of file sitkPixelIDTypeLists.h.

◆ BasicPixelIDTypeList

typedef typelist::MakeTypeList<BasicPixelID<int8_t>, BasicPixelID<uint8_t>, BasicPixelID<int16_t>, BasicPixelID<uint16_t>, BasicPixelID<int32_t>, BasicPixelID<uint32_t>, BasicPixelID<float>, BasicPixelID<double> >::Type itk::simple::BasicPixelIDTypeList

List of all pixel ids for the itk::Image class.

Todo:: address vnl issues with long long types

See also: BasicPixelID

Definition at line 53 of file sitkPixelIDTypeLists.h.

◆ ComplexPixelIDTypeList

typedef typelist::MakeTypeList< BasicPixelID<std::complex< float > >, BasicPixelID<std::complex< double > > >::Type itk::simple::ComplexPixelIDTypeList

List of pixel ids which are std::complex types for the itk::Image class.

See also: BasicPixelID

Definition at line 103 of file sitkPixelIDTypeLists.h.

◆ FalseType

using itk::simple::FalseType = typedef std::false_type

Definition at line 32 of file sitkPixelIDTokens.h.

◆ InstantiatedPixelIDTypeList

using itk::simple::InstantiatedPixelIDTypeList = typedef AllPixelIDTypeList

List of pixel ids which are instantiated for use in SimpleITK

this include image of itk::Image,itk::VectorImage, and itk::LabelMap types.

See also: BasicPixelID; VectorPixelID; LabelPixelID

Definition at line 207 of file sitkPixelIDTypeLists.h.

◆ IntegerLabelPixelIDTypeList

using itk::simple::IntegerLabelPixelIDTypeList = typedef UnsignedIntegerPixelIDTypeList

Definition at line 167 of file sitkPixelIDTypeLists.h.

◆ IntegerPixelIDTypeList

typedef typelist::MakeTypeList<BasicPixelID<int8_t>, BasicPixelID<uint8_t>, BasicPixelID<int16_t>, BasicPixelID<uint16_t>, BasicPixelID<int32_t>, BasicPixelID<uint32_t> >::Type itk::simple::IntegerPixelIDTypeList

List of pixel ids which are integer types for the itk::Image class.

See also: BasicPixelID

Definition at line 76 of file sitkPixelIDTypeLists.h.

◆ LabelPixelIDTypeList

typedef typelist::MakeTypeList<LabelPixelID<uint8_t>, LabelPixelID<uint16_t>, LabelPixelID<uint32_t> >::Type itk::simple::LabelPixelIDTypeList

List of pixel ids which are for itk::LabelMap Image class.

See also: LabelPixelID

Definition at line 165 of file sitkPixelIDTypeLists.h.

◆ NonLabelPixelIDTypeList

typedef typelist::Append< typelist::Append< BasicPixelIDTypeList, ComplexPixelIDTypeList >::Type, VectorPixelIDTypeList >::Type itk::simple::NonLabelPixelIDTypeList

List of all pixel ids available, but itk::LabelMap this include image of itk::Image, itk::VectorImage

See also: BasicPixelID; VectorPixelID; LabelPixelID

Definition at line 180 of file sitkPixelIDTypeLists.h.

◆ PixelIDValueType

using itk::simple::PixelIDValueType = typedef int

Definition at line 32 of file sitkPixelIDValues.h.

◆ RealPixelIDTypeList

typedef typelist::MakeTypeList<BasicPixelID<float>, BasicPixelID<double> >::Type itk::simple::RealPixelIDTypeList

List of pixel ids which are real types for the itk::Image class.

See also: BasicPixelID

Definition at line 96 of file sitkPixelIDTypeLists.h.

◆ RealVectorPixelIDTypeList

typedef typelist::MakeTypeList<VectorPixelID<float>, VectorPixelID<double> >::Type itk::simple::RealVectorPixelIDTypeList

List of pixel ids which are real vectors for itk::VectorImage class.

See also: VectorPixelID

Definition at line 142 of file sitkPixelIDTypeLists.h.

◆ ScalarPixelIDTypeList

using itk::simple::ScalarPixelIDTypeList = typedef BasicPixelIDTypeList

List of all single valued images of the itk::Image class.

See also: BasicPixelID

Definition at line 59 of file sitkPixelIDTypeLists.h.

◆ SignedPixelIDTypeList

typedef typelist::MakeTypeList<BasicPixelID<int8_t>, BasicPixelID<int16_t>, BasicPixelID<int32_t>, BasicPixelID<float>, BasicPixelID<double> >::Type itk::simple::SignedPixelIDTypeList

List of pixel ids which are signed

See also: BasicPixelID

Definition at line 116 of file sitkPixelIDTypeLists.h.

◆ SignedVectorPixelIDTypeList

typedef typelist::MakeTypeList< VectorPixelID<int8_t>, VectorPixelID<int16_t>, VectorPixelID<int32_t>, VectorPixelID<float>, VectorPixelID<double> >::Type itk::simple::SignedVectorPixelIDTypeList

List of pixel ids which are signed of vectors

See also: BasicPixelID

Definition at line 152 of file sitkPixelIDTypeLists.h.

◆ TrueType

using itk::simple::TrueType = typedef std::true_type

Definition at line 31 of file sitkPixelIDTokens.h.

◆ UnsignedIntegerPixelIDTypeList

typedef typelist::MakeTypeList<BasicPixelID<uint8_t>, BasicPixelID<uint16_t>, BasicPixelID<uint32_t> >::Type itk::simple::UnsignedIntegerPixelIDTypeList

List of pixel ids which are unsigned integer types for the itk::Image class.

See also: BasicPixelID

Definition at line 88 of file sitkPixelIDTypeLists.h.

◆ VectorPixelIDTypeList

typedef typelist::MakeTypeList<VectorPixelID<int8_t>, VectorPixelID<uint8_t>, VectorPixelID<int16_t>, VectorPixelID<uint16_t>, VectorPixelID<int32_t>, VectorPixelID<uint32_t>, VectorPixelID<float>, VectorPixelID<double> >::Type itk::simple::VectorPixelIDTypeList

List of pixel ids which are vectors for itk::VectorImage class.

See also: VectorPixelID

Definition at line 134 of file sitkPixelIDTypeLists.h.

Enumeration Type Documentation

◆ EventEnum

enum itk::simple::EventEnum

Events which can be observed from ProcessObject.

For more information see the page CommandPage.

Enumerator
sitkAnyEvent	Occurs for all event types.
sitkAbortEvent	Occurs after the process has been aborted, but before exiting the Execute method.
sitkDeleteEvent	Occurs when the underlying itk::ProcessObject is deleted.
sitkEndEvent	Occurs at then end of normal processing.
sitkIterationEvent	Occurs with some algorithms that run for a fixed or undetermined number of iterations.
sitkProgressEvent	Occurs when the progress changes in most process objects.
sitkStartEvent	Occurs when then itk::ProcessObject is starting.
sitkMultiResolutionIterationEvent	Occurs when some filters change processing to a different scale. Note This event is a sub-event of the more general IterationEvent. The general iteration event will also be invoked.
sitkUserEvent	Other events may fall into this enumeration.

Examples: FilterProgressReporting/FilterProgressReporting.cs, FilterProgressReporting/FilterProgressReporting.java, ImageRegistrationMethod1/ImageRegistrationMethod1.cs, ImageRegistrationMethod1/ImageRegistrationMethod1.java, and ImageRegistrationMethod2/ImageRegistrationMethod2.cs.

Definition at line 31 of file sitkEvent.h.

◆ InterpolatorEnum

enum itk::simple::InterpolatorEnum

Enumerator
sitkNearestNeighbor	Nearest-neighbor interpolation. See also itk::NearestNeighborInterpolateImageFunction
sitkLinear	N-D linear interpolation. See also itk::LinearInterpolateImageFunction
sitkBSpline	B-Spline of order 3 interpolation. See also itk::BSplineInterpolateImageFunction
sitkGaussian	Gaussian interpolation. Sigma is set to 0.8 input pixels and alpha is 4.0 See also itk::GaussianInterpolateImageFunction
sitkLabelGaussian	Smoothly interpolate multi-label images. Sigma is set to 1.0 input pixels and alpha is 1.0 See also itk:LabelImageGaussianInterpolateImageFunction
sitkHammingWindowedSinc	Windowed sinc interpolation. \[ w(x) = 0.54 + 0.46 cos(\frac{\pi x}{m} ) \] See also itk::WindowedSincInterpolateImageFunction itk::Function::HammingWindowFunction
sitkCosineWindowedSinc	Windowed sinc interpolation. \[ w(x) = cos(\frac{\pi x}{2 m} ) \] See also itk::WindowedSincInterpolateImageFunction itk::Function::CosineWindowFunction
sitkWelchWindowedSinc	Windowed sinc interpolation. \[ w(x) = 1 - ( \frac{x^2}{m^2} ) \] See also itk::WindowedSincInterpolateImageFunction itk::Function::WelchWindowFunction
sitkLanczosWindowedSinc	Windowed sinc interpolation. \[ w(x) = \textrm{sinc} ( \frac{x}{m} ) \] See also itk::WindowedSincInterpolateImageFunction itk::Function::LanczosWindowFunction
sitkBlackmanWindowedSinc	Windowed sinc interpolation. \[ w(x) = 0.42 + 0.5 cos(\frac{\pi x}{m}) + 0.08 cos(\frac{2 \pi x}{m}) \] See also itk::WindowedSincInterpolateImageFunction itk::Function::BlackmanWindowFunction
sitkBSplineResampler	Interpolator for a BSpline coefficient image. This interpolator should be used with the resampling the image intensities of a BSpline coefficient image. The order specifies the order of the coefficient image, and defaults to 3. See also BSplineTransformation itk::BSplineResampleImageFunction
sitkBSplineResamplerOrder3
sitkBSplineResamplerOrder1
sitkBSplineResamplerOrder2
sitkBSplineResamplerOrder4
sitkBSplineResamplerOrder5

Examples: ImageRegistrationMethod1/ImageRegistrationMethod1.cs, ImageRegistrationMethod1/ImageRegistrationMethod1.java, and ImageRegistrationMethod2/ImageRegistrationMethod2.cs.

Definition at line 30 of file sitkInterpolator.h.

◆ KernelEnum

enum itk::simple::KernelEnum

Enumerator
sitkAnnulus
sitkBall
sitkBox
sitkCross
sitkPolygon3
sitkPolygon4
sitkPolygon5
sitkPolygon6
sitkPolygon7
sitkPolygon8
sitkPolygon9

Definition at line 29 of file sitkKernel.h.

◆ PixelIDValueEnum

enum itk::simple::PixelIDValueEnum

Enumerated values of pixelIDs.

Each PixelID's value corresponds to the index of the PixelID type, in the type list "InstantiatedPixelIDTypeList". It is possible that different configurations for SimpleITK could result in different values for pixelID. So these enumerated values should be used.

Additionally, not all PixelID an instantiated in for the tool kit. If a PixelID is not instantiated then it's value is -1. Therefore it is likely that multiple elements in the enumeration will have a zero value. Therefore the first preferred method is to use "if" statements, with the first branch checking for the Unknown value.

If a switch case statement is needed the ConditionalValue meta-programming object can be used as follows:

switch( pixelIDValue )
   {
 case sitk::sitkUnknown:
   // handle exceptional case
   break
 case sitk::ConditionalValue< sitk::sitkUInt8 != sitk::sitkUnknown, sitk::sitkUInt8, -2 >::Value:
   ...
   break;
 case sitk::ConditionalValue< sitk::sitkInt8 != sitk::sitkUnknown, sitk::sitkInt8, -3 >::Value:
   ...
   break;
 case sitk::ConditionalValue< sitk::N != sitk::sitkUnknown, sitk::N, -N >::Value:
   ...
   break;
 default:
    // handle another exceptional case
   }

Enumerator
sitkUnknown
sitkUInt8	Unsigned 8 bit integer.
sitkInt8	Signed 8 bit integer.
sitkUInt16	Unsigned 16 bit integer.
sitkInt16	Signed 16 bit integer.
sitkUInt32	Unsigned 32 bit integer.
sitkInt32	Signed 32 bit integer.
sitkUInt64	Unsigned 64 bit integer.
sitkInt64	Signed 64 bit integer.
sitkFloat32	32 bit float
sitkFloat64	64 bit float
sitkComplexFloat32	compelex number of 32 bit float
sitkComplexFloat64	compelex number of 64 bit float
sitkVectorUInt8	Multi-component of unsigned 8 bit integer.
sitkVectorInt8	Multi-component of signed 8 bit integer.
sitkVectorUInt16	Multi-component of unsigned 16 bit integer.
sitkVectorInt16	Multi-component of signed 16 bit integer.
sitkVectorUInt32	Multi-component of unsigned 32 bit integer.
sitkVectorInt32	Multi-component of signed 32 bit integer.
sitkVectorUInt64	Multi-component of unsigned 64 bit integer.
sitkVectorInt64	Multi-component of signed 64 bit integer.
sitkVectorFloat32	Multi-component of 32 bit float.
sitkVectorFloat64	Multi-component of 64 bit float.
sitkLabelUInt8	RLE label of unsigned 8 bit integers.
sitkLabelUInt16	RLE label of unsigned 16 bit integers.
sitkLabelUInt32	RLE label of unsigned 32 bit integers.
sitkLabelUInt64	RLE label of unsigned 64 bit integers.

Examples: CSharp/CannySegmentationLevelSetImageFilter.cs, CSharp/ConnectedThresholdSegmentation.cs, FastMarchingSegmentation/FastMarchingSegmentation.cs, HelloWorld/HelloWorld.cs, HelloWorld/HelloWorld.java, ImageRegistrationMethod1/ImageRegistrationMethod1.cs, ImageRegistrationMethod1/ImageRegistrationMethod1.java, and ImageRegistrationMethod2/ImageRegistrationMethod2.cs.

Definition at line 90 of file sitkPixelIDValues.h.

◆ SeedEnum

enum itk::simple::SeedEnum

Enumerator
sitkWallClock	A sentinel value used for "seed" parameters to indicate it should be initialized by the wall clock for pseudo-random behavior.

Definition at line 28 of file sitkRandomSeed.h.

◆ TransformEnum

enum itk::simple::TransformEnum

Enumerator
sitkUnknownTransform
sitkIdentity
sitkTranslation
sitkScale
sitkScaleLogarithmic
sitkEuler
sitkSimilarity
sitkQuaternionRigid
sitkVersor
sitkVersorRigid
sitkScaleSkewVersor
sitkScaleVersor
sitkAffine
sitkComposite
sitkDisplacementField
sitkBSplineTransform

Definition at line 43 of file sitkTransform.h.

Function Documentation

◆ Abs() [1/2]

Image itk::simple::Abs ( const Image & image1 )

Computes the absolute value of each pixel.

\ This function directly calls the execute method of AbsImageFilter in order to support a procedural API

See also: itk::simple::AbsImageFilter for the object oriented interface

◆ Abs() [2/2]

Image itk::simple::Abs ( Image && image1 )

Computes the absolute value of each pixel.

\ This function directly calls the execute method of AbsImageFilter in order to support a procedural API

See also: itk::simple::AbsImageFilter for the object oriented interface

◆ AbsoluteValueDifference() [1/5]

Image itk::simple::AbsoluteValueDifference	(	const Image &	image1,
		const Image &	image2
	)

Implements pixel-wise the computation of absolute value difference.

\ This function directly calls the execute method of AbsoluteValueDifferenceImageFilter in order to support a procedural API

See also: itk::simple::AbsoluteValueDifferenceImageFilter for the object oriented interface

◆ AbsoluteValueDifference() [2/5]

Image itk::simple::AbsoluteValueDifference	(	const Image &	image1,
		double	constant
	)

◆ AbsoluteValueDifference() [3/5]

Image itk::simple::AbsoluteValueDifference	(	double	constant,
		const Image &	image2
	)

◆ AbsoluteValueDifference() [4/5]

Image itk::simple::AbsoluteValueDifference	(	Image &&	image1,
		const Image &	image2
	)

Implements pixel-wise the computation of absolute value difference.

\ This function directly calls the execute method of AbsoluteValueDifferenceImageFilter in order to support a procedural API

See also: itk::simple::AbsoluteValueDifferenceImageFilter for the object oriented interface

◆ AbsoluteValueDifference() [5/5]

Image itk::simple::AbsoluteValueDifference	(	Image &&	image1,
		double	constant
	)

◆ Acos() [1/2]

Image itk::simple::Acos ( const Image & image1 )

Computes the inverse cosine of each pixel.

\ This function directly calls the execute method of AcosImageFilter in order to support a procedural API

See also: itk::simple::AcosImageFilter for the object oriented interface

◆ Acos() [2/2]

Image itk::simple::Acos ( Image && image1 )

Computes the inverse cosine of each pixel.

\ This function directly calls the execute method of AcosImageFilter in order to support a procedural API

See also: itk::simple::AcosImageFilter for the object oriented interface

◆ AdaptiveHistogramEqualization()

Image itk::simple::AdaptiveHistogramEqualization	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 5)`,
		float	alpha = `0.3f`,
		float	beta = `0.3f`
	)

Power Law Adaptive Histogram Equalization.

\ This function directly calls the execute method of AdaptiveHistogramEqualizationImageFilter in order to support a procedural API

See also: itk::simple::AdaptiveHistogramEqualizationImageFilter for the object oriented interface

Examples: SliceBySliceDecorator/SliceBySliceDecorator.cxx.

◆ Add() [1/5]

Image itk::simple::Add	(	const Image &	image1,
		const Image &	image2
	)

Pixel-wise addition of two images.

\ This function directly calls the execute method of AddImageFilter in order to support a procedural API

See also: itk::simple::AddImageFilter for the object oriented interface

◆ Add() [2/5]

Image itk::simple::Add	(	const Image &	image1,
		double	constant
	)

◆ Add() [3/5]

Image itk::simple::Add	(	double	constant,
		const Image &	image2
	)

◆ Add() [4/5]

Image itk::simple::Add	(	Image &&	image1,
		const Image &	image2
	)

Pixel-wise addition of two images.

\ This function directly calls the execute method of AddImageFilter in order to support a procedural API

See also: itk::simple::AddImageFilter for the object oriented interface

Referenced by operator+(), and operator+=().

◆ Add() [5/5]

Image itk::simple::Add	(	Image &&	image1,
		double	constant
	)

◆ AdditiveGaussianNoise() [1/2]

Image itk::simple::AdditiveGaussianNoise	(	const Image &	image1,
		double	standardDeviation = `1.0`,
		double	mean = `0.0`,
		uint32_t	seed = `(uint32_t) itk::simple::sitkWallClock`
	)

Alter an image with additive Gaussian white noise.

\ This function directly calls the execute method of AdditiveGaussianNoiseImageFilter in order to support a procedural API

See also: itk::simple::AdditiveGaussianNoiseImageFilter for the object oriented interface

◆ AdditiveGaussianNoise() [2/2]

Image itk::simple::AdditiveGaussianNoise	(	Image &&	image1,
		double	standardDeviation = `1.0`,
		double	mean = `0.0`,
		uint32_t	seed = `(uint32_t) itk::simple::sitkWallClock`
	)

Alter an image with additive Gaussian white noise.

\ This function directly calls the execute method of AdditiveGaussianNoiseImageFilter in order to support a procedural API

See also: itk::simple::AdditiveGaussianNoiseImageFilter for the object oriented interface

◆ AggregateLabelMap() [1/2]

Image itk::simple::AggregateLabelMap ( const Image & image1 )

Collapses all labels into the first label.

\ This function directly calls the execute method of AggregateLabelMapFilter in order to support a procedural API

See also: itk::simple::AggregateLabelMapFilter for the object oriented interface

◆ AggregateLabelMap() [2/2]

Image itk::simple::AggregateLabelMap ( Image && image1 )

Collapses all labels into the first label.

\ This function directly calls the execute method of AggregateLabelMapFilter in order to support a procedural API

See also: itk::simple::AggregateLabelMapFilter for the object oriented interface

◆ And() [1/5]

Image itk::simple::And	(	const Image &	image1,
		const Image &	image2
	)

Implements the AND bitwise operator pixel-wise between two images.

\ This function directly calls the execute method of AndImageFilter in order to support a procedural API

See also: itk::simple::AndImageFilter for the object oriented interface

◆ And() [2/5]

Image itk::simple::And	(	const Image &	image1,
		int	constant
	)

◆ And() [3/5]

Image itk::simple::And	(	Image &&	image1,
		const Image &	image2
	)

Implements the AND bitwise operator pixel-wise between two images.

\ This function directly calls the execute method of AndImageFilter in order to support a procedural API

See also: itk::simple::AndImageFilter for the object oriented interface

Referenced by operator&(), and operator&=().

◆ And() [4/5]

Image itk::simple::And	(	Image &&	image1,
		int	constant
	)

◆ And() [5/5]

Image itk::simple::And	(	int	constant,
		const Image &	image2
	)

◆ AntiAliasBinary() [1/2]

Image itk::simple::AntiAliasBinary	(	const Image &	image1,
		double	maximumRMSError = `0.07`,
		uint32_t	numberOfIterations = `1000u`
	)

A method for estimation of a surface from a binary volume.

\ This function directly calls the execute method of AntiAliasBinaryImageFilter in order to support a procedural API

See also: itk::simple::AntiAliasBinaryImageFilter for the object oriented interface

◆ AntiAliasBinary() [2/2]

Image itk::simple::AntiAliasBinary	(	Image &&	image1,
		double	maximumRMSError = `0.07`,
		uint32_t	numberOfIterations = `1000u`
	)

A method for estimation of a surface from a binary volume.

\ This function directly calls the execute method of AntiAliasBinaryImageFilter in order to support a procedural API

See also: itk::simple::AntiAliasBinaryImageFilter for the object oriented interface

◆ ApproximateSignedDistanceMap()

Image itk::simple::ApproximateSignedDistanceMap	(	const Image &	image1,
		double	insideValue = `1u`,
		double	outsideValue = `0u`
	)

Create a map of the approximate signed distance from the boundaries of a binary image.

\ This function directly calls the execute method of ApproximateSignedDistanceMapImageFilter in order to support a procedural API

See also: itk::simple::ApproximateSignedDistanceMapImageFilter for the object oriented interface

◆ Asin() [1/2]

Image itk::simple::Asin ( const Image & image1 )

Computes the sine of each pixel.

\ This function directly calls the execute method of AsinImageFilter in order to support a procedural API

See also: itk::simple::AsinImageFilter for the object oriented interface

◆ Asin() [2/2]

Image itk::simple::Asin ( Image && image1 )

Computes the sine of each pixel.

\ This function directly calls the execute method of AsinImageFilter in order to support a procedural API

See also: itk::simple::AsinImageFilter for the object oriented interface

◆ Atan() [1/2]

Image itk::simple::Atan ( const Image & image1 )

Computes the one-argument inverse tangent of each pixel.

\ This function directly calls the execute method of AtanImageFilter in order to support a procedural API

See also: itk::simple::AtanImageFilter for the object oriented interface

◆ Atan() [2/2]

Image itk::simple::Atan ( Image && image1 )

Computes the one-argument inverse tangent of each pixel.

\ This function directly calls the execute method of AtanImageFilter in order to support a procedural API

See also: itk::simple::AtanImageFilter for the object oriented interface

◆ Atan2() [1/5]

Image itk::simple::Atan2	(	const Image &	image1,
		const Image &	image2
	)

Computes two argument inverse tangent.

\ This function directly calls the execute method of Atan2ImageFilter in order to support a procedural API

See also: itk::simple::Atan2ImageFilter for the object oriented interface

◆ Atan2() [2/5]

Image itk::simple::Atan2	(	const Image &	image1,
		double	constant
	)

◆ Atan2() [3/5]

Image itk::simple::Atan2	(	double	constant,
		const Image &	image2
	)

◆ Atan2() [4/5]

Image itk::simple::Atan2	(	Image &&	image1,
		const Image &	image2
	)

Computes two argument inverse tangent.

\ This function directly calls the execute method of Atan2ImageFilter in order to support a procedural API

See also: itk::simple::Atan2ImageFilter for the object oriented interface

◆ Atan2() [5/5]

Image itk::simple::Atan2	(	Image &&	image1,
		double	constant
	)

◆ Bilateral()

Image itk::simple::Bilateral	(	const Image &	image1,
		double	domainSigma = `4.0`,
		double	rangeSigma = `50.0`,
		unsigned int	numberOfRangeGaussianSamples = `100u`
	)

Blurs an image while preserving edges.

\ This function directly calls the execute method of BilateralImageFilter in order to support a procedural API

See also: itk::simple::BilateralImageFilter for the object oriented interface

◆ BinaryClosingByReconstruction()

Image itk::simple::BinaryClosingByReconstruction	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		double	foregroundValue = `1.0`,
		bool	fullyConnected = `false`
	)

binary closing by reconstruction of an image.

\ This function directly calls the execute method of BinaryClosingByReconstructionImageFilter in order to support a procedural API

See also: itk::simple::BinaryClosingByReconstructionImageFilter for the object oriented interface

◆ BinaryContour() [1/2]

Image itk::simple::BinaryContour	(	const Image &	image1,
		bool	fullyConnected = `false`,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`
	)

Labels the pixels on the border of the objects in a binary image.

\ This function directly calls the execute method of BinaryContourImageFilter in order to support a procedural API

See also: itk::simple::BinaryContourImageFilter for the object oriented interface

◆ BinaryContour() [2/2]

Image itk::simple::BinaryContour	(	Image &&	image1,
		bool	fullyConnected = `false`,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`
	)

Labels the pixels on the border of the objects in a binary image.

\ This function directly calls the execute method of BinaryContourImageFilter in order to support a procedural API

See also: itk::simple::BinaryContourImageFilter for the object oriented interface

◆ BinaryDilate()

Image itk::simple::BinaryDilate	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`,
		bool	boundaryToForeground = `false`
	)

Fast binary dilation of a single intensity value in the image.

\ This function directly calls the execute method of BinaryDilateImageFilter in order to support a procedural API

See also: itk::simple::BinaryDilateImageFilter for the object oriented interface

◆ BinaryErode()

Image itk::simple::BinaryErode	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`,
		bool	boundaryToForeground = `true`
	)

Fast binary erosion of a single intensity value in the image.

\ This function directly calls the execute method of BinaryErodeImageFilter in order to support a procedural API

See also: itk::simple::BinaryErodeImageFilter for the object oriented interface

◆ BinaryFillhole()

Image itk::simple::BinaryFillhole	(	const Image &	image1,
		bool	fullyConnected = `false`,
		double	foregroundValue = `1.0`
	)

Remove holes not connected to the boundary of the image.

\ This function directly calls the execute method of BinaryFillholeImageFilter in order to support a procedural API

See also: itk::simple::BinaryFillholeImageFilter for the object oriented interface

◆ BinaryGrindPeak()

Image itk::simple::BinaryGrindPeak	(	const Image &	image1,
		bool	fullyConnected = `false`,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0`
	)

Remove the objects not connected to the boundary of the image.

\ This function directly calls the execute method of BinaryGrindPeakImageFilter in order to support a procedural API

See also: itk::simple::BinaryGrindPeakImageFilter for the object oriented interface

◆ BinaryImageToLabelMap()

Image itk::simple::BinaryImageToLabelMap	(	const Image &	image1,
		bool	fullyConnected = `false`,
		double	inputForegroundValue = `1.0`,
		double	outputBackgroundValue = `0.0`
	)

Label the connected components in a binary image and produce a collection of label objects.

\ This function directly calls the execute method of BinaryImageToLabelMapFilter in order to support a procedural API

See also: itk::simple::BinaryImageToLabelMapFilter for the object oriented interface

◆ BinaryMagnitude() [1/2]

Image itk::simple::BinaryMagnitude	(	const Image &	image1,
		const Image &	image2
	)

Computes the square root of the sum of squares of corresponding input pixels.

\ This function directly calls the execute method of BinaryMagnitudeImageFilter in order to support a procedural API

See also: itk::simple::BinaryMagnitudeImageFilter for the object oriented interface

◆ BinaryMagnitude() [2/2]

Image itk::simple::BinaryMagnitude	(	Image &&	image1,
		const Image &	image2
	)

Computes the square root of the sum of squares of corresponding input pixels.

\ This function directly calls the execute method of BinaryMagnitudeImageFilter in order to support a procedural API

See also: itk::simple::BinaryMagnitudeImageFilter for the object oriented interface

◆ BinaryMedian()

Image itk::simple::BinaryMedian	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0.0`
	)

Applies a version of the median filter optimized for binary images.

\ This function directly calls the execute method of BinaryMedianImageFilter in order to support a procedural API

See also: itk::simple::BinaryMedianImageFilter for the object oriented interface

◆ BinaryMinMaxCurvatureFlow() [1/2]

Image itk::simple::BinaryMinMaxCurvatureFlow	(	const Image &	image1,
		double	timeStep = `0.05`,
		uint32_t	numberOfIterations = `5u`,
		int	stencilRadius = `2`,
		double	threshold = `0.0`
	)

Denoise a binary image using min/max curvature flow.

\ This function directly calls the execute method of BinaryMinMaxCurvatureFlowImageFilter in order to support a procedural API

See also: itk::simple::BinaryMinMaxCurvatureFlowImageFilter for the object oriented interface

◆ BinaryMinMaxCurvatureFlow() [2/2]

Image itk::simple::BinaryMinMaxCurvatureFlow	(	Image &&	image1,
		double	timeStep = `0.05`,
		uint32_t	numberOfIterations = `5u`,
		int	stencilRadius = `2`,
		double	threshold = `0.0`
	)

Denoise a binary image using min/max curvature flow.

\ This function directly calls the execute method of BinaryMinMaxCurvatureFlowImageFilter in order to support a procedural API

See also: itk::simple::BinaryMinMaxCurvatureFlowImageFilter for the object oriented interface

◆ BinaryMorphologicalClosing()

Image itk::simple::BinaryMorphologicalClosing	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		double	foregroundValue = `1.0`,
		bool	safeBorder = `true`
	)

binary morphological closing of an image.

\ This function directly calls the execute method of BinaryMorphologicalClosingImageFilter in order to support a procedural API

See also: itk::simple::BinaryMorphologicalClosingImageFilter for the object oriented interface

◆ BinaryMorphologicalOpening()

Image itk::simple::BinaryMorphologicalOpening	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`
	)

binary morphological opening of an image.

\ This function directly calls the execute method of BinaryMorphologicalOpeningImageFilter in order to support a procedural API

See also: itk::simple::BinaryMorphologicalOpeningImageFilter for the object oriented interface

◆ BinaryNot() [1/2]

Image itk::simple::BinaryNot	(	const Image &	image1,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0.0`
	)

Implements the BinaryNot logical operator pixel-wise between two images.

\ This function directly calls the execute method of BinaryNotImageFilter in order to support a procedural API

See also: itk::simple::BinaryNotImageFilter for the object oriented interface

◆ BinaryNot() [2/2]

Image itk::simple::BinaryNot	(	Image &&	image1,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0.0`
	)

Implements the BinaryNot logical operator pixel-wise between two images.

\ This function directly calls the execute method of BinaryNotImageFilter in order to support a procedural API

See also: itk::simple::BinaryNotImageFilter for the object oriented interface

◆ BinaryOpeningByReconstruction()

Image itk::simple::BinaryOpeningByReconstruction	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0.0`,
		bool	fullyConnected = `false`
	)

binary morphological closing of an image.

\ This function directly calls the execute method of BinaryOpeningByReconstructionImageFilter in order to support a procedural API

See also: itk::simple::BinaryOpeningByReconstructionImageFilter for the object oriented interface

◆ BinaryProjection()

Image itk::simple::BinaryProjection	(	const Image &	image1,
		unsigned int	projectionDimension = `0u`,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0.0`
	)

Binary projection.

\ This function directly calls the execute method of BinaryProjectionImageFilter in order to support a procedural API

See also: itk::simple::BinaryProjectionImageFilter for the object oriented interface

◆ BinaryPruning()

Image itk::simple::BinaryPruning	(	const Image &	image1,
		uint32_t	iteration = `3u`
	)

This filter removes "spurs" of less than a certain length in the input image.

\ This function directly calls the execute method of BinaryPruningImageFilter in order to support a procedural API

See also: itk::simple::BinaryPruningImageFilter for the object oriented interface

◆ BinaryReconstructionByDilation()

Image itk::simple::BinaryReconstructionByDilation	(	const Image &	markerImage,
		const Image &	maskImage,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`,
		bool	fullyConnected = `false`
	)

binary reconstruction by dilation of an image

\ This function directly calls the execute method of BinaryReconstructionByDilationImageFilter in order to support a procedural API

See also: itk::simple::BinaryReconstructionByDilationImageFilter for the object oriented interface

◆ BinaryReconstructionByErosion()

Image itk::simple::BinaryReconstructionByErosion	(	const Image &	markerImage,
		const Image &	maskImage,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`,
		bool	fullyConnected = `false`
	)

binary reconstruction by erosion of an image

\ This function directly calls the execute method of BinaryReconstructionByErosionImageFilter in order to support a procedural API

See also: itk::simple::BinaryReconstructionByErosionImageFilter for the object oriented interface

◆ BinaryThinning()

Image itk::simple::BinaryThinning ( const Image & image1 )

This filter computes one-pixel-wide edges of the input image.

\ This function directly calls the execute method of BinaryThinningImageFilter in order to support a procedural API

See also: itk::simple::BinaryThinningImageFilter for the object oriented interface

◆ BinaryThreshold() [1/2]

Image itk::simple::BinaryThreshold	(	const Image &	image1,
		double	lowerThreshold = `0.0`,
		double	upperThreshold = `255.0`,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`
	)

Binarize an input image by thresholding.

\ This function directly calls the execute method of BinaryThresholdImageFilter in order to support a procedural API

See also: itk::simple::BinaryThresholdImageFilter for the object oriented interface

◆ BinaryThreshold() [2/2]

Image itk::simple::BinaryThreshold	(	Image &&	image1,
		double	lowerThreshold = `0.0`,
		double	upperThreshold = `255.0`,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`
	)

Binarize an input image by thresholding.

\ This function directly calls the execute method of BinaryThresholdImageFilter in order to support a procedural API

See also: itk::simple::BinaryThresholdImageFilter for the object oriented interface

Examples: HelloWorld/HelloWorld.cxx.

◆ BinaryThresholdProjection()

Image itk::simple::BinaryThresholdProjection	(	const Image &	image1,
		unsigned int	projectionDimension = `0u`,
		double	thresholdValue = `0.0`,
		uint8_t	foregroundValue = `1u`,
		uint8_t	backgroundValue = `0u`
	)

BinaryThreshold projection.

\ This function directly calls the execute method of BinaryThresholdProjectionImageFilter in order to support a procedural API

See also: itk::simple::BinaryThresholdProjectionImageFilter for the object oriented interface

◆ BinomialBlur()

Image itk::simple::BinomialBlur	(	const Image &	image1,
		unsigned int	repetitions = `1u`
	)

Performs a separable blur on each dimension of an image.

\ This function directly calls the execute method of BinomialBlurImageFilter in order to support a procedural API

See also: itk::simple::BinomialBlurImageFilter for the object oriented interface

◆ BinShrink()

Image itk::simple::BinShrink	(	const Image &	image1,
		std::vector< unsigned int >	shrinkFactors = `std::vector< unsigned int >(3, 1)`
	)

Reduce the size of an image by an integer factor in each dimension while performing averaging of an input neighborhood.

\ This function directly calls the execute method of BinShrinkImageFilter in order to support a procedural API

See also: itk::simple::BinShrinkImageFilter for the object oriented interface

◆ BitwiseNot() [1/2]

Image itk::simple::BitwiseNot ( const Image & image1 )

Implements pixel-wise generic operation on one image.

\ This function directly calls the execute method of BitwiseNotImageFilter in order to support a procedural API

See also: itk::simple::BitwiseNotImageFilter for the object oriented interface

◆ BitwiseNot() [2/2]

Image itk::simple::BitwiseNot ( Image && image1 )

Implements pixel-wise generic operation on one image.

\ This function directly calls the execute method of BitwiseNotImageFilter in order to support a procedural API

See also: itk::simple::BitwiseNotImageFilter for the object oriented interface

Referenced by operator~().

◆ BlackTopHat()

Image itk::simple::BlackTopHat	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		bool	safeBorder = `true`
	)

Black top hat extracts local minima that are smaller than the structuring element.

\ This function directly calls the execute method of BlackTopHatImageFilter in order to support a procedural API

See also: itk::simple::BlackTopHatImageFilter for the object oriented interface

◆ BoundedReciprocal() [1/2]

Image itk::simple::BoundedReciprocal ( const Image & image1 )

Computes 1/(1+x) for each pixel in the image.

\ This function directly calls the execute method of BoundedReciprocalImageFilter in order to support a procedural API

See also: itk::simple::BoundedReciprocalImageFilter for the object oriented interface

◆ BoundedReciprocal() [2/2]

Image itk::simple::BoundedReciprocal ( Image && image1 )

Computes 1/(1+x) for each pixel in the image.

\ This function directly calls the execute method of BoundedReciprocalImageFilter in order to support a procedural API

See also: itk::simple::BoundedReciprocalImageFilter for the object oriented interface

◆ BoxMean()

Image itk::simple::BoxMean	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`
	)

Implements a fast rectangular mean filter using the accumulator approach.

\ This function directly calls the execute method of BoxMeanImageFilter in order to support a procedural API

See also: itk::simple::BoxMeanImageFilter for the object oriented interface

◆ BoxSigma()

Image itk::simple::BoxSigma	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`
	)

Implements a fast rectangular sigma filter using the accumulator approach.

\ This function directly calls the execute method of BoxSigmaImageFilter in order to support a procedural API

See also: itk::simple::BoxSigmaImageFilter for the object oriented interface

◆ BSplineDecomposition()

Image itk::simple::BSplineDecomposition	(	const Image &	image1,
		uint32_t	splineOrder = `3u`
	)

Calculates the B-Spline coefficients of an image. Spline order may be from 0 to 5.

\ This function directly calls the execute method of BSplineDecompositionImageFilter in order to support a procedural API

See also: itk::simple::BSplineDecompositionImageFilter for the object oriented interface

◆ BSplineTransformInitializer()

BSplineTransform itk::simple::BSplineTransformInitializer	(	const Image &	image1,
		const std::vector< uint32_t > &	transformDomainMeshSize = `std::vector< uint32_t >(3, 1u)`,
		unsigned int	order = `3u`
	)

BSplineTransformInitializerFilter is a helper class intended to initialize the control point grid such that it has a physically consistent definition. It sets the transform domain origin, physical dimensions and direction from information obtained from the image. It also sets the mesh size if asked to do so by calling SetTransformDomainMeshSize()before calling InitializeTransform().

This function directly calls the execute method of BSplineTransformInitializerFilter in order to support a procedural API

See also: itk::simple::BSplineTransformInitializerFilter for the object oriented interface

Examples: ImageRegistrationMethodBSpline1/ImageRegistrationMethodBSpline1.cxx, and ImageRegistrationMethodBSpline3/ImageRegistrationMethodBSpline3.cxx.

◆ CannyEdgeDetection()

Image itk::simple::CannyEdgeDetection	(	const Image &	image1,
		double	lowerThreshold = `0.0`,
		double	upperThreshold = `0.0`,
		std::vector< double >	variance = `std::vector< double >(3, 0.0)`,
		std::vector< double >	maximumError = `std::vector< double >(3, 0.01)`
	)

This filter is an implementation of a Canny edge detector for scalar-valued images.

\ This function directly calls the execute method of CannyEdgeDetectionImageFilter in order to support a procedural API

See also: itk::simple::CannyEdgeDetectionImageFilter for the object oriented interface

◆ CannySegmentationLevelSet() [1/2]

Image itk::simple::CannySegmentationLevelSet	(	const Image &	initialImage,
		const Image &	featureImage,
		double	threshold = `0.0`,
		double	variance = `0.0`,
		double	maximumRMSError = `0.02`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		double	advectionScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`,
		double	isoSurfaceValue = `0.0`
	)

Segments structures in images based on image features derived from pseudo-canny-edges.

\ This function directly calls the execute method of CannySegmentationLevelSetImageFilter in order to support a procedural API

See also: itk::simple::CannySegmentationLevelSetImageFilter for the object oriented interface

◆ CannySegmentationLevelSet() [2/2]

Image itk::simple::CannySegmentationLevelSet	(	Image &&	initialImage,
		const Image &	featureImage,
		double	threshold = `0.0`,
		double	variance = `0.0`,
		double	maximumRMSError = `0.02`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		double	advectionScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`,
		double	isoSurfaceValue = `0.0`
	)

Segments structures in images based on image features derived from pseudo-canny-edges.

\ This function directly calls the execute method of CannySegmentationLevelSetImageFilter in order to support a procedural API

See also: itk::simple::CannySegmentationLevelSetImageFilter for the object oriented interface

◆ Cast()

Image itk::simple::Cast	(	const Image &	image,
		PixelIDValueEnum	pixelID
	)

Examples: CppInPlace/CppInPlace.cxx, and SimpleGaussianFunctional.cxx.

◆ CenteredTransformInitializer()

Transform itk::simple::CenteredTransformInitializer	(	const Image &	fixedImage,
		const Image &	movingImage,
		const Transform &	transform,
		CenteredTransformInitializerFilter::OperationModeType	operationMode = `itk::simple::CenteredTransformInitializerFilter::MOMENTS`
	)

CenteredTransformInitializer is a helper class intended to initialize the center of rotation and the translation of Transforms having the center of rotation among their parameters.

This function directly calls the execute method of CenteredTransformInitializerFilter in order to support a procedural API

See also: itk::simple::CenteredTransformInitializerFilter for the object oriented interface

Examples: ImageRegistrationMethodDisplacement1/ImageRegistrationMethodDisplacement1.cxx.

◆ CenteredVersorTransformInitializer()

Transform itk::simple::CenteredVersorTransformInitializer	(	const Image &	fixedImage,
		const Image &	movingImage,
		const Transform &	transform,
		bool	computeRotation = `false`
	)

CenteredVersorTransformInitializer is a helper class intended to initialize the center of rotation, versor, and translation of the VersorRigid3DTransform.

This function directly calls the execute method of CenteredVectorTransformInitializerFilter in order to support a procedural API.

See also: itk::simple::CenteredVersorTransformInitializerFilter for the object oriented interface

◆ ChangeLabel() [1/2]

Image itk::simple::ChangeLabel	(	const Image &	image1,
		std::map< double, double >	changeMap = `std::map< double, double >()`
	)

Change Sets of Labels.

\ This function directly calls the execute method of ChangeLabelImageFilter in order to support a procedural API

See also: itk::simple::ChangeLabelImageFilter for the object oriented interface

◆ ChangeLabel() [2/2]

Image itk::simple::ChangeLabel	(	Image &&	image1,
		std::map< double, double >	changeMap = `std::map< double, double >()`
	)

Change Sets of Labels.

\ This function directly calls the execute method of ChangeLabelImageFilter in order to support a procedural API

See also: itk::simple::ChangeLabelImageFilter for the object oriented interface

◆ ChangeLabelLabelMap() [1/2]

Image itk::simple::ChangeLabelLabelMap	(	const Image &	image1,
		std::map< double, double >	changeMap = `std::map< double, double >()`
	)

Replace the label Ids of selected LabelObjects with new label Ids.

\ This function directly calls the execute method of ChangeLabelLabelMapFilter in order to support a procedural API

See also: itk::simple::ChangeLabelLabelMapFilter for the object oriented interface

◆ ChangeLabelLabelMap() [2/2]

Image itk::simple::ChangeLabelLabelMap	(	Image &&	image1,
		std::map< double, double >	changeMap = `std::map< double, double >()`
	)

Replace the label Ids of selected LabelObjects with new label Ids.

\ This function directly calls the execute method of ChangeLabelLabelMapFilter in order to support a procedural API

See also: itk::simple::ChangeLabelLabelMapFilter for the object oriented interface

◆ CheckerBoard()

Image itk::simple::CheckerBoard	(	const Image &	image1,
		const Image &	image2,
		std::vector< uint32_t >	checkerPattern = `std::vector< uint32_t >(3, 4)`
	)

Combines two images in a checkerboard pattern.

\ This function directly calls the execute method of CheckerBoardImageFilter in order to support a procedural API

See also: itk::simple::CheckerBoardImageFilter for the object oriented interface

◆ Clamp() [1/2]

Image itk::simple::Clamp	(	const Image &	image1,
		PixelIDValueEnum	outputPixelType = `itk::simple::sitkUnknown`,
		double	lowerBound = `-std::numeric_limits< double >::max()`,
		double	upperBound = `std::numeric_limits< double >::max()`
	)

Casts input pixels to output pixel type and clamps the output pixel values to a specified range.

\ This function directly calls the execute method of ClampImageFilter in order to support a procedural API

See also: itk::simple::ClampImageFilter for the object oriented interface

◆ Clamp() [2/2]

Image itk::simple::Clamp	(	Image &&	image1,
		PixelIDValueEnum	outputPixelType = `itk::simple::sitkUnknown`,
		double	lowerBound = `-std::numeric_limits< double >::max()`,
		double	upperBound = `std::numeric_limits< double >::max()`
	)

Casts input pixels to output pixel type and clamps the output pixel values to a specified range.

\ This function directly calls the execute method of ClampImageFilter in order to support a procedural API

See also: itk::simple::ClampImageFilter for the object oriented interface

◆ ClosingByReconstruction()

Image itk::simple::ClosingByReconstruction	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		bool	fullyConnected = `false`,
		bool	preserveIntensities = `false`
	)

Closing by reconstruction of an image.

\ This function directly calls the execute method of ClosingByReconstructionImageFilter in order to support a procedural API

See also: itk::simple::ClosingByReconstructionImageFilter for the object oriented interface

◆ CollidingFronts()

Image itk::simple::CollidingFronts	(	const Image &	image1,
		std::vector< std::vector< unsigned int > >	seedPoints1 = `std::vector< std::vector< unsigned int > >()`,
		std::vector< std::vector< unsigned int > >	seedPoints2 = `std::vector< std::vector< unsigned int > >()`,
		bool	applyConnectivity = `true`,
		double	negativeEpsilon = `-1e-6`,
		bool	stopOnTargets = `false`
	)

Selects a region of space where two independent fronts run towards each other.

\ This function directly calls the execute method of CollidingFrontsImageFilter in order to support a procedural API

See also: itk::simple::CollidingFrontsImageFilter for the object oriented interface

◆ ComplexToImaginary() [1/2]

Image itk::simple::ComplexToImaginary ( const Image & image1 )

Computes pixel-wise the imaginary part of a complex image.

\ This function directly calls the execute method of ComplexToImaginaryImageFilter in order to support a procedural API

See also: itk::simple::ComplexToImaginaryImageFilter for the object oriented interface

◆ ComplexToImaginary() [2/2]

Image itk::simple::ComplexToImaginary ( Image && image1 )

Computes pixel-wise the imaginary part of a complex image.

\ This function directly calls the execute method of ComplexToImaginaryImageFilter in order to support a procedural API

See also: itk::simple::ComplexToImaginaryImageFilter for the object oriented interface

◆ ComplexToModulus() [1/2]

Image itk::simple::ComplexToModulus ( const Image & image1 )

Computes pixel-wise the Modulus of a complex image.

\ This function directly calls the execute method of ComplexToModulusImageFilter in order to support a procedural API

See also: itk::simple::ComplexToModulusImageFilter for the object oriented interface

◆ ComplexToModulus() [2/2]

Image itk::simple::ComplexToModulus ( Image && image1 )

Computes pixel-wise the Modulus of a complex image.

\ This function directly calls the execute method of ComplexToModulusImageFilter in order to support a procedural API

See also: itk::simple::ComplexToModulusImageFilter for the object oriented interface

◆ ComplexToPhase() [1/2]

Image itk::simple::ComplexToPhase ( const Image & image1 )

Computes pixel-wise the modulus of a complex image.

\ This function directly calls the execute method of ComplexToPhaseImageFilter in order to support a procedural API

See also: itk::simple::ComplexToPhaseImageFilter for the object oriented interface

◆ ComplexToPhase() [2/2]

Image itk::simple::ComplexToPhase ( Image && image1 )

Computes pixel-wise the modulus of a complex image.

\ This function directly calls the execute method of ComplexToPhaseImageFilter in order to support a procedural API

See also: itk::simple::ComplexToPhaseImageFilter for the object oriented interface

◆ ComplexToReal() [1/2]

Image itk::simple::ComplexToReal ( const Image & image1 )

Computes pixel-wise the real(x) part of a complex image.

\ This function directly calls the execute method of ComplexToRealImageFilter in order to support a procedural API

See also: itk::simple::ComplexToRealImageFilter for the object oriented interface

◆ ComplexToReal() [2/2]

Image itk::simple::ComplexToReal ( Image && image1 )

Computes pixel-wise the real(x) part of a complex image.

\ This function directly calls the execute method of ComplexToRealImageFilter in order to support a procedural API

See also: itk::simple::ComplexToRealImageFilter for the object oriented interface

◆ Compose() [1/6]

Image itk::simple::Compose ( const Image & image1 )

ComposeImageFilter combine several scalar images into a multicomponent image.

This function directly calls the execute method of ComposeImageFilter in order to support a procedural API

See also: itk::simple::ComposeImageFilter for the object oriented interface

◆ Compose() [2/6]

Image itk::simple::Compose	(	const Image &	image1,
		const Image &	image2
	)

ComposeImageFilter combine several scalar images into a multicomponent image.

This function directly calls the execute method of ComposeImageFilter in order to support a procedural API

See also: itk::simple::ComposeImageFilter for the object oriented interface

◆ Compose() [3/6]

Image itk::simple::Compose	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3
	)

ComposeImageFilter combine several scalar images into a multicomponent image.

This function directly calls the execute method of ComposeImageFilter in order to support a procedural API

See also: itk::simple::ComposeImageFilter for the object oriented interface

◆ Compose() [4/6]

Image itk::simple::Compose	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4
	)

ComposeImageFilter combine several scalar images into a multicomponent image.

This function directly calls the execute method of ComposeImageFilter in order to support a procedural API

See also: itk::simple::ComposeImageFilter for the object oriented interface

◆ Compose() [5/6]

Image itk::simple::Compose	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5
	)

ComposeImageFilter combine several scalar images into a multicomponent image.

This function directly calls the execute method of ComposeImageFilter in order to support a procedural API

See also: itk::simple::ComposeImageFilter for the object oriented interface

◆ Compose() [6/6]

Image itk::simple::Compose ( const std::vector< Image > & images )

ComposeImageFilter combine several scalar images into a multicomponent image.

This function directly calls the execute method of ComposeImageFilter in order to support a procedural API

See also: itk::simple::ComposeImageFilter for the object oriented interface

◆ ConfidenceConnected()

Image itk::simple::ConfidenceConnected	(	const Image &	image1,
		std::vector< std::vector< unsigned int > >	seedList = `std::vector< std::vector< unsigned int > >()`,
		unsigned int	numberOfIterations = `4u`,
		double	multiplier = `4.5`,
		unsigned int	initialNeighborhoodRadius = `1u`,
		uint8_t	replaceValue = `1u`
	)

Segment pixels with similar statistics using connectivity.

\ This function directly calls the execute method of ConfidenceConnectedImageFilter in order to support a procedural API

See also: itk::simple::ConfidenceConnectedImageFilter for the object oriented interface

◆ ConnectedComponent() [1/2]

Image itk::simple::ConnectedComponent	(	const Image &	image,
		bool	fullyConnected = `false`
	)

Label the objects in a binary image.

\ This function directly calls the execute method of ConnectedComponentImageFilter in order to support a procedural API

See also: itk::simple::ConnectedComponentImageFilter for the object oriented interface

◆ ConnectedComponent() [2/2]

Image itk::simple::ConnectedComponent	(	const Image &	image,
		const Image &	maskImage,
		bool	fullyConnected = `false`
	)

Label the objects in a binary image.

\ This function directly calls the execute method of ConnectedComponentImageFilter in order to support a procedural API

See also: itk::simple::ConnectedComponentImageFilter for the object oriented interface

◆ ConnectedThreshold()

Image itk::simple::ConnectedThreshold	(	const Image &	image1,
		std::vector< std::vector< unsigned int > >	seedList = `std::vector< std::vector< unsigned int > >()`,
		double	lower = `0`,
		double	upper = `1`,
		uint8_t	replaceValue = `1u`,
		ConnectedThresholdImageFilter::ConnectivityType	connectivity = `itk::simple::ConnectedThresholdImageFilter::FaceConnectivity`
	)

Label pixels that are connected to a seed and lie within a range of values.

\ This function directly calls the execute method of ConnectedThresholdImageFilter in order to support a procedural API

See also: itk::simple::ConnectedThresholdImageFilter for the object oriented interface

◆ ConstantPad()

Image itk::simple::ConstantPad	(	const Image &	image1,
		std::vector< unsigned int >	padLowerBound = `std::vector< unsigned int >(3, 0)`,
		std::vector< unsigned int >	padUpperBound = `std::vector< unsigned int >(3, 0)`,
		double	constant = `0.0`
	)

Increase the image size by padding with a constant value.

\ This function directly calls the execute method of ConstantPadImageFilter in order to support a procedural API

See also: itk::simple::ConstantPadImageFilter for the object oriented interface

◆ Convolution()

Image itk::simple::Convolution	(	const Image &	image,
		const Image &	kernelImage,
		bool	normalize = `false`,
		ConvolutionImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::ConvolutionImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		ConvolutionImageFilter::OutputRegionModeType	outputRegionMode = `itk::simple::ConvolutionImageFilter::SAME`
	)

Convolve a given image with an arbitrary image kernel.

\ This function directly calls the execute method of ConvolutionImageFilter in order to support a procedural API

See also: itk::simple::ConvolutionImageFilter for the object oriented interface

◆ Cos() [1/2]

Image itk::simple::Cos ( const Image & image1 )

Computes the cosine of each pixel.

\ This function directly calls the execute method of CosImageFilter in order to support a procedural API

See also: itk::simple::CosImageFilter for the object oriented interface

◆ Cos() [2/2]

Image itk::simple::Cos ( Image && image1 )

Computes the cosine of each pixel.

\ This function directly calls the execute method of CosImageFilter in order to support a procedural API

See also: itk::simple::CosImageFilter for the object oriented interface

◆ CreateKernel()

template<unsigned int VImageDimension>

itk::FlatStructuringElement< VImageDimension > itk::simple::CreateKernel	(	KernelEnum	kernelType,
		const std::vector< uint32_t > &	size
	)

Definition at line 36 of file sitkCreateKernel.h.

References sitkAnnulus, sitkBall, sitkBox, sitkCross, sitkExceptionMacro, and sitkKernelPolygonCreateMacro.

◆ Crop() [1/2]

Image itk::simple::Crop	(	const Image &	image1,
		std::vector< unsigned int >	lowerBoundaryCropSize = `std::vector< unsigned int >(3, 0)`,
		std::vector< unsigned int >	upperBoundaryCropSize = `std::vector< unsigned int >(3, 0)`
	)

Decrease the image size by cropping the image by an itk::Size at both the upper and lower bounds of the largest possible region.

\ This function directly calls the execute method of CropImageFilter in order to support a procedural API

See also: itk::simple::CropImageFilter for the object oriented interface

◆ Crop() [2/2]

Image itk::simple::Crop	(	Image &&	image1,
		std::vector< unsigned int >	lowerBoundaryCropSize = `std::vector< unsigned int >(3, 0)`,
		std::vector< unsigned int >	upperBoundaryCropSize = `std::vector< unsigned int >(3, 0)`
	)

Decrease the image size by cropping the image by an itk::Size at both the upper and lower bounds of the largest possible region.

\ This function directly calls the execute method of CropImageFilter in order to support a procedural API

See also: itk::simple::CropImageFilter for the object oriented interface

Referenced by itk::simple::LabelMapMaskImageFilter::SetCrop().

◆ CurvatureAnisotropicDiffusion() [1/2]

Image itk::simple::CurvatureAnisotropicDiffusion	(	const Image &	image1,
		double	timeStep = `0.0625`,
		double	conductanceParameter = `3.0`,
		unsigned int	conductanceScalingUpdateInterval = `1u`,
		uint32_t	numberOfIterations = `5u`
	)

itk::simple::CurvatureAnisotropicDiffusionImageFilter Procedural Interface

\ This function directly calls the execute method of CurvatureAnisotropicDiffusionImageFilter in order to support a procedural API

See also: itk::simple::CurvatureAnisotropicDiffusionImageFilter for the object oriented interface

◆ CurvatureAnisotropicDiffusion() [2/2]

Image itk::simple::CurvatureAnisotropicDiffusion	(	Image &&	image1,
		double	timeStep = `0.0625`,
		double	conductanceParameter = `3.0`,
		unsigned int	conductanceScalingUpdateInterval = `1u`,
		uint32_t	numberOfIterations = `5u`
	)

itk::simple::CurvatureAnisotropicDiffusionImageFilter Procedural Interface

\ This function directly calls the execute method of CurvatureAnisotropicDiffusionImageFilter in order to support a procedural API

See also: itk::simple::CurvatureAnisotropicDiffusionImageFilter for the object oriented interface

◆ CurvatureFlow() [1/2]

Image itk::simple::CurvatureFlow	(	const Image &	image1,
		double	timeStep = `0.05`,
		uint32_t	numberOfIterations = `5u`
	)

Denoise an image using curvature driven flow.

\ This function directly calls the execute method of CurvatureFlowImageFilter in order to support a procedural API

See also: itk::simple::CurvatureFlowImageFilter for the object oriented interface

◆ CurvatureFlow() [2/2]

Image itk::simple::CurvatureFlow	(	Image &&	image1,
		double	timeStep = `0.05`,
		uint32_t	numberOfIterations = `5u`
	)

Denoise an image using curvature driven flow.

\ This function directly calls the execute method of CurvatureFlowImageFilter in order to support a procedural API

See also: itk::simple::CurvatureFlowImageFilter for the object oriented interface

◆ CyclicShift()

Image itk::simple::CyclicShift	(	const Image &	image1,
		std::vector< int >	shift = `std::vector< int >(3, 0)`
	)

Perform a cyclic spatial shift of image intensities on the image grid.

\ This function directly calls the execute method of CyclicShiftImageFilter in order to support a procedural API

See also: itk::simple::CyclicShiftImageFilter for the object oriented interface

◆ DanielssonDistanceMap()

Image itk::simple::DanielssonDistanceMap	(	const Image &	image1,
		bool	inputIsBinary = `false`,
		bool	squaredDistance = `false`,
		bool	useImageSpacing = `false`
	)

This filter computes the distance map of the input image as an approximation with pixel accuracy to the Euclidean distance.

\ This function directly calls the execute method of DanielssonDistanceMapImageFilter in order to support a procedural API

See also: itk::simple::DanielssonDistanceMapImageFilter for the object oriented interface

◆ Derivative()

Image itk::simple::Derivative	(	const Image &	image1,
		unsigned int	direction = `0u`,
		unsigned int	order = `1u`,
		bool	useImageSpacing = `true`
	)

Computes the directional derivative of an image. The directional derivative at each pixel location is computed by convolution with a derivative operator of user-specified order.

\ This function directly calls the execute method of DerivativeImageFilter in order to support a procedural API

See also: itk::simple::DerivativeImageFilter for the object oriented interface

◆ DICOMOrient()

Image itk::simple::DICOMOrient	(	const Image &	image1,
		std::string	desiredCoordinateOrientation = `std::string("LPS")`
	)

Permute axes and flip images as needed to obtain an approximation to the desired orientation.

\ This function directly calls the execute method of DICOMOrientImageFilter in order to support a procedural API

See also: itk::simple::DICOMOrientImageFilter for the object oriented interface

◆ DilateObjectMorphology()

Image itk::simple::DilateObjectMorphology	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		double	objectValue = `1`
	)

dilation of an object in an image

\ This function directly calls the execute method of DilateObjectMorphologyImageFilter in order to support a procedural API

See also: itk::simple::DilateObjectMorphologyImageFilter for the object oriented interface

◆ DiscreteGaussian() [1/2]

Image itk::simple::DiscreteGaussian	(	const Image &	image1,
		double	variance,
		unsigned int	maximumKernelWidth = `32u`,
		double	maximumError = `0.01`,
		bool	useImageSpacing = `true`
	)

Blurs an image by separable convolution with discrete gaussian kernels. This filter performs Gaussian blurring by separable convolution of an image and a discrete Gaussian operator (kernel).

This function directly calls the execute method of DiscreteGaussianImageFilter in order to support a procedural API

See also: itk::simple::DiscreteGaussianImageFilter for the object oriented interface

Examples: ImageRegistrationMethod2/ImageRegistrationMethod2.cxx.

◆ DiscreteGaussian() [2/2]

Image itk::simple::DiscreteGaussian	(	const Image &	image1,
		std::vector< double >	variance = `std::vector< double >(3, 1.0)`,
		unsigned int	maximumKernelWidth = `32u`,
		std::vector< double >	maximumError = `std::vector< double >(3, 0.01)`,
		bool	useImageSpacing = `true`
	)

Blurs an image by separable convolution with discrete gaussian kernels. This filter performs Gaussian blurring by separable convolution of an image and a discrete Gaussian operator (kernel).

\ This function directly calls the execute method of DiscreteGaussianImageFilter in order to support a procedural API

See also: itk::simple::DiscreteGaussianImageFilter for the object oriented interface

◆ DiscreteGaussianDerivative()

Image itk::simple::DiscreteGaussianDerivative	(	const Image &	image1,
		std::vector< double >	variance = `std::vector< double >(3, 0.0)`,
		std::vector< unsigned int >	order = `std::vector< unsigned int >(3, 1)`,
		unsigned int	maximumKernelWidth = `32u`,
		double	maximumError = `0.01`,
		bool	useImageSpacing = `true`,
		bool	normalizeAcrossScale = `false`
	)

Calculates image derivatives using discrete derivative gaussian kernels. This filter calculates Gaussian derivative by separable convolution of an image and a discrete Gaussian derivative operator (kernel).

\ This function directly calls the execute method of DiscreteGaussianDerivativeImageFilter in order to support a procedural API

See also: itk::simple::DiscreteGaussianDerivativeImageFilter for the object oriented interface

◆ DisplacementFieldJacobianDeterminant()

Image itk::simple::DisplacementFieldJacobianDeterminant	(	const Image &	image1,
		bool	useImageSpacing = `true`,
		std::vector< double >	derivativeWeights = `std::vector< double >()`
	)

Computes a scalar image from a vector image (e.g., deformation field) input, where each output scalar at each pixel is the Jacobian determinant of the vector field at that location. This calculation is correct in the case where the vector image is a "displacement" from the current location. The computation for the jacobian determinant is: det[ dT/dx ] = det[ I + du/dx ].

\ This function directly calls the execute method of DisplacementFieldJacobianDeterminantFilter in order to support a procedural API

See also: itk::simple::DisplacementFieldJacobianDeterminantFilter for the object oriented interface

◆ Divide() [1/5]

Image itk::simple::Divide	(	const Image &	image1,
		const Image &	image2
	)

Pixel-wise division of two images.

\ This function directly calls the execute method of DivideImageFilter in order to support a procedural API

See also: itk::simple::DivideImageFilter for the object oriented interface

◆ Divide() [2/5]

Image itk::simple::Divide	(	const Image &	image1,
		double	constant
	)

◆ Divide() [3/5]

Image itk::simple::Divide	(	double	constant,
		const Image &	image2
	)

◆ Divide() [4/5]

Image itk::simple::Divide	(	Image &&	image1,
		const Image &	image2
	)

Pixel-wise division of two images.

\ This function directly calls the execute method of DivideImageFilter in order to support a procedural API

See also: itk::simple::DivideImageFilter for the object oriented interface

Referenced by operator/(), and operator/=().

◆ Divide() [5/5]

Image itk::simple::Divide	(	Image &&	image1,
		double	constant
	)

◆ DivideFloor() [1/5]

Image itk::simple::DivideFloor	(	const Image &	image1,
		const Image &	image2
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of DivideFloorImageFilter in order to support a procedural API

See also: itk::simple::DivideFloorImageFilter for the object oriented interface

◆ DivideFloor() [2/5]

Image itk::simple::DivideFloor	(	const Image &	image1,
		double	constant
	)

◆ DivideFloor() [3/5]

Image itk::simple::DivideFloor	(	double	constant,
		const Image &	image2
	)

◆ DivideFloor() [4/5]

Image itk::simple::DivideFloor	(	Image &&	image1,
		const Image &	image2
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of DivideFloorImageFilter in order to support a procedural API

See also: itk::simple::DivideFloorImageFilter for the object oriented interface

◆ DivideFloor() [5/5]

Image itk::simple::DivideFloor	(	Image &&	image1,
		double	constant
	)

◆ DivideReal() [1/5]

Image itk::simple::DivideReal	(	const Image &	image1,
		const Image &	image2
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of DivideRealImageFilter in order to support a procedural API

See also: itk::simple::DivideRealImageFilter for the object oriented interface

◆ DivideReal() [2/5]

Image itk::simple::DivideReal	(	const Image &	image1,
		double	constant
	)

◆ DivideReal() [3/5]

Image itk::simple::DivideReal	(	double	constant,
		const Image &	image2
	)

◆ DivideReal() [4/5]

Image itk::simple::DivideReal	(	Image &&	image1,
		const Image &	image2
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of DivideRealImageFilter in order to support a procedural API

See also: itk::simple::DivideRealImageFilter for the object oriented interface

◆ DivideReal() [5/5]

Image itk::simple::DivideReal	(	Image &&	image1,
		double	constant
	)

◆ DoubleThreshold()

Image itk::simple::DoubleThreshold	(	const Image &	image1,
		double	threshold1 = `0.0`,
		double	threshold2 = `1.0`,
		double	threshold3 = `254.0`,
		double	threshold4 = `255.0`,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		bool	fullyConnected = `false`
	)

Binarize an input image using double thresholding.

\ This function directly calls the execute method of DoubleThresholdImageFilter in order to support a procedural API

See also: itk::simple::DoubleThresholdImageFilter for the object oriented interface

◆ EdgePotential() [1/2]

Image itk::simple::EdgePotential ( const Image & image1 )

Computes the edge potential of an image from the image gradient.

\ This function directly calls the execute method of EdgePotentialImageFilter in order to support a procedural API

See also: itk::simple::EdgePotentialImageFilter for the object oriented interface

◆ EdgePotential() [2/2]

Image itk::simple::EdgePotential ( Image && image1 )

Computes the edge potential of an image from the image gradient.

\ This function directly calls the execute method of EdgePotentialImageFilter in order to support a procedural API

See also: itk::simple::EdgePotentialImageFilter for the object oriented interface

◆ Equal() [1/5]

Image itk::simple::Equal	(	const Image &	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of EqualImageFilter in order to support a procedural API

See also: itk::simple::EqualImageFilter for the object oriented interface

◆ Equal() [2/5]

Image itk::simple::Equal	(	const Image &	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ Equal() [3/5]

Image itk::simple::Equal	(	double	constant,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ Equal() [4/5]

Image itk::simple::Equal	(	Image &&	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of EqualImageFilter in order to support a procedural API

See also: itk::simple::EqualImageFilter for the object oriented interface

◆ Equal() [5/5]

Image itk::simple::Equal	(	Image &&	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ ErodeObjectMorphology()

Image itk::simple::ErodeObjectMorphology	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		double	objectValue = `1`,
		double	backgroundValue = `0`
	)

Erosion of an object in an image.

\ This function directly calls the execute method of ErodeObjectMorphologyImageFilter in order to support a procedural API

See also: itk::simple::ErodeObjectMorphologyImageFilter for the object oriented interface

◆ Exp() [1/2]

Image itk::simple::Exp ( const Image & image1 )

Computes the exponential function of each pixel.

\ This function directly calls the execute method of ExpImageFilter in order to support a procedural API

See also: itk::simple::ExpImageFilter for the object oriented interface

◆ Exp() [2/2]

Image itk::simple::Exp ( Image && image1 )

Computes the exponential function of each pixel.

\ This function directly calls the execute method of ExpImageFilter in order to support a procedural API

See also: itk::simple::ExpImageFilter for the object oriented interface

◆ Expand()

Image itk::simple::Expand	(	const Image &	image1,
		std::vector< unsigned int >	expandFactors = `std::vector< unsigned int >(3, 1)`,
		InterpolatorEnum	interpolator = `itk::simple::sitkLinear`
	)

Expand the size of an image by an integer factor in each dimension.

\ This function directly calls the execute method of ExpandImageFilter in order to support a procedural API

See also: itk::simple::ExpandImageFilter for the object oriented interface

◆ ExpNegative() [1/2]

Image itk::simple::ExpNegative ( const Image & image1 )

Computes the function exp(-K.x) for each input pixel.

\ This function directly calls the execute method of ExpNegativeImageFilter in order to support a procedural API

See also: itk::simple::ExpNegativeImageFilter for the object oriented interface

◆ ExpNegative() [2/2]

Image itk::simple::ExpNegative ( Image && image1 )

Computes the function exp(-K.x) for each input pixel.

\ This function directly calls the execute method of ExpNegativeImageFilter in order to support a procedural API

See also: itk::simple::ExpNegativeImageFilter for the object oriented interface

◆ Extract() [1/2]

Image itk::simple::Extract	(	const Image &	image1,
		std::vector< unsigned int >	size = `std::vector< unsigned int >(SITK_MAX_DIMENSION, 1)`,
		std::vector< int >	index = `std::vector< int >(SITK_MAX_DIMENSION, 0)`,
		ExtractImageFilter::DirectionCollapseToStrategyType	directionCollapseToStrategy = `itk::simple::ExtractImageFilter::DIRECTIONCOLLAPSETOGUESS`
	)

Decrease the image size by cropping the image to the selected region bounds.

\ This function directly calls the execute method of ExtractImageFilter in order to support a procedural API

See also: itk::simple::ExtractImageFilter for the object oriented interface

◆ Extract() [2/2]

Image itk::simple::Extract	(	Image &&	image1,
		std::vector< unsigned int >	size = `std::vector< unsigned int >(SITK_MAX_DIMENSION, 1)`,
		std::vector< int >	index = `std::vector< int >(SITK_MAX_DIMENSION, 0)`,
		ExtractImageFilter::DirectionCollapseToStrategyType	directionCollapseToStrategy = `itk::simple::ExtractImageFilter::DIRECTIONCOLLAPSETOGUESS`
	)

Decrease the image size by cropping the image to the selected region bounds.

\ This function directly calls the execute method of ExtractImageFilter in order to support a procedural API

See also: itk::simple::ExtractImageFilter for the object oriented interface

◆ FastApproximateRank()

Image itk::simple::FastApproximateRank	(	const Image &	image1,
		double	rank = `0.5`,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`
	)

A separable rank filter.

\ This function directly calls the execute method of FastApproximateRankImageFilter in order to support a procedural API

See also: itk::simple::FastApproximateRankImageFilter for the object oriented interface

◆ FastMarching()

Image itk::simple::FastMarching	(	const Image &	image1,
		std::vector< std::vector< unsigned int > >	trialPoints = `std::vector< std::vector< unsigned int > >()`,
		double	normalizationFactor = `1.0`,
		double	stoppingValue = `std::numeric_limits< double >::max()/2.0`
	)

Solve an Eikonal equation using Fast Marching.

\ This function directly calls the execute method of FastMarchingImageFilter in order to support a procedural API

See also: itk::simple::FastMarchingImageFilter for the object oriented interface

◆ FastMarchingBase()

Image itk::simple::FastMarchingBase	(	const Image &	image1,
		std::vector< std::vector< unsigned int > >	trialPoints = `std::vector< std::vector< unsigned int > >()`,
		double	normalizationFactor = `1.0`,
		double	stoppingValue = `std::numeric_limits< float >::max()/2.0`,
		FastMarchingBaseImageFilter::TopologyCheckType	topologyCheck = `itk::simple::FastMarchingBaseImageFilter::Nothing`
	)

Apply the Fast Marching method to solve an Eikonal equation on an image.

\ This function directly calls the execute method of FastMarchingBaseImageFilter in order to support a procedural API

See also: itk::simple::FastMarchingBaseImageFilter for the object oriented interface

◆ FastMarchingUpwindGradient()

Image itk::simple::FastMarchingUpwindGradient	(	const Image &	image1,
		std::vector< std::vector< unsigned int > >	trialPoints = `std::vector< std::vector< unsigned int > >()`,
		unsigned int	numberOfTargets = `0u`,
		std::vector< std::vector< unsigned int > >	targetPoints = `std::vector< std::vector< unsigned int > >()`,
		double	targetOffset = `1.0`,
		double	normalizationFactor = `1.0`
	)

Generates the upwind gradient field of fast marching arrival times.

\ This function directly calls the execute method of FastMarchingUpwindGradientImageFilter in order to support a procedural API

See also: itk::simple::FastMarchingUpwindGradientImageFilter for the object oriented interface

◆ FFTConvolution()

Image itk::simple::FFTConvolution	(	const Image &	image,
		const Image &	kernelImage,
		bool	normalize = `false`,
		FFTConvolutionImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::FFTConvolutionImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		FFTConvolutionImageFilter::OutputRegionModeType	outputRegionMode = `itk::simple::FFTConvolutionImageFilter::SAME`
	)

Convolve a given image with an arbitrary image kernel using multiplication in the Fourier domain.

\ This function directly calls the execute method of FFTConvolutionImageFilter in order to support a procedural API

See also: itk::simple::FFTConvolutionImageFilter for the object oriented interface

◆ FFTNormalizedCorrelation()

Image itk::simple::FFTNormalizedCorrelation	(	const Image &	image1,
		const Image &	image2,
		uint64_t	requiredNumberOfOverlappingPixels = `0u`
	)

Calculate normalized cross correlation using FFTs.

\ This function directly calls the execute method of FFTNormalizedCorrelationImageFilter in order to support a procedural API

See also: itk::simple::FFTNormalizedCorrelationImageFilter for the object oriented interface

◆ FFTPad()

Image itk::simple::FFTPad	(	const Image &	image1,
		FFTPadImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::FFTPadImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		int	sizeGreatestPrimeFactor = `5`
	)

Pad an image to make it suitable for an FFT transformation.

\ This function directly calls the execute method of FFTPadImageFilter in order to support a procedural API

See also: itk::simple::FFTPadImageFilter for the object oriented interface

◆ FFTShift()

Image itk::simple::FFTShift	(	const Image &	image1,
		bool	inverse = `false`
	)

Shift the zero-frequency components of a Fourier transform to the center of the image.

\ This function directly calls the execute method of FFTShiftImageFilter in order to support a procedural API

See also: itk::simple::FFTShiftImageFilter for the object oriented interface

◆ Flip()

Image itk::simple::Flip	(	const Image &	image1,
		std::vector< bool >	flipAxes = `std::vector< bool >(3, false)`,
		bool	flipAboutOrigin = `false`
	)

Flips an image across user specified axes.

\ This function directly calls the execute method of FlipImageFilter in order to support a procedural API

See also: itk::simple::FlipImageFilter for the object oriented interface

◆ ForwardFFT()

Image itk::simple::ForwardFFT ( const Image & image1 )

Base class for forward Fast Fourier Transform .

\ This function directly calls the execute method of ForwardFFTImageFilter in order to support a procedural API

See also: itk::simple::ForwardFFTImageFilter for the object oriented interface

◆ GaborSource()

Image itk::simple::GaborSource	(	PixelIDValueEnum	outputPixelType = `itk::simple::sitkFloat32`,
		std::vector< unsigned int >	size = `std::vector< unsigned int >(3, 64)`,
		std::vector< double >	sigma = `std::vector< double >(3, 16.0)`,
		std::vector< double >	mean = `std::vector< double >(3, 32.0)`,
		double	frequency = `0.4`,
		std::vector< double >	origin = `std::vector< double >(3, 0.0)`,
		std::vector< double >	spacing = `std::vector< double >(3, 1.0)`,
		std::vector< double >	direction = `std::vector< double >()`
	)

Generate an n-dimensional image of a Gabor filter.

This function directly calls the execute method of GaborImageSource in order to support a procedural API

See also: itk::simple::GaborImageSource for the object oriented interface

◆ GaussianSource()

Image itk::simple::GaussianSource	(	PixelIDValueEnum	outputPixelType = `itk::simple::sitkFloat32`,
		std::vector< unsigned int >	size = `std::vector< unsigned int >(3, 64)`,
		std::vector< double >	sigma = `std::vector< double >(3, 16.0)`,
		std::vector< double >	mean = `std::vector< double >(3, 32.0)`,
		double	scale = `255`,
		std::vector< double >	origin = `std::vector< double >(3, 0.0)`,
		std::vector< double >	spacing = `std::vector< double >(3, 1.0)`,
		std::vector< double >	direction = `std::vector< double >()`,
		bool	normalized = `false`
	)

Generate an n-dimensional image of a Gaussian.

This function directly calls the execute method of GaussianImageSource in order to support a procedural API

See also: itk::simple::GaussianImageSource for the object oriented interface

Examples: CppCMake/Source/sitk_example.cxx, and HelloWorld/HelloWorld.cxx.

◆ GeodesicActiveContourLevelSet() [1/2]

Image itk::simple::GeodesicActiveContourLevelSet	(	const Image &	initialImage,
		const Image &	featureImage,
		double	maximumRMSError = `0.01`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		double	advectionScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`
	)

Segments structures in images based on a user supplied edge potential map.

\ This function directly calls the execute method of GeodesicActiveContourLevelSetImageFilter in order to support a procedural API

See also: itk::simple::GeodesicActiveContourLevelSetImageFilter for the object oriented interface

◆ GeodesicActiveContourLevelSet() [2/2]

Image itk::simple::GeodesicActiveContourLevelSet	(	Image &&	initialImage,
		const Image &	featureImage,
		double	maximumRMSError = `0.01`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		double	advectionScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`
	)

Segments structures in images based on a user supplied edge potential map.

\ This function directly calls the execute method of GeodesicActiveContourLevelSetImageFilter in order to support a procedural API

See also: itk::simple::GeodesicActiveContourLevelSetImageFilter for the object oriented interface

◆ GetImageFromVectorImage()

template<typename TPixelType , unsigned int ImageDimension>

SITKCommon_HIDDEN itk::Image< itk::Vector< TPixelType, ImageDimension >, ImageDimension>::Pointer itk::simple::GetImageFromVectorImage	(	itk::VectorImage< TPixelType, ImageDimension > *	img,
		bool	transferOwnership = `false`
	)

A utility method to help convert between itk image types efficiently.

◆ GetPixelIDValueAsString() [1/2]

const std::string SITKCommon_EXPORT itk::simple::GetPixelIDValueAsString ( PixelIDValueEnum type )

◆ GetPixelIDValueAsString() [2/2]

const std::string SITKCommon_EXPORT itk::simple::GetPixelIDValueAsString ( PixelIDValueType type )

Referenced by itk::simple::ProcessObject::CastImageToITK().

◆ GetPixelIDValueFromString()

PixelIDValueType SITKCommon_EXPORT itk::simple::GetPixelIDValueFromString ( const std::string & enumString )

Function mapping enumeration names in std::string to values.

This function is intended for use by the R bindings. R stores the enumeration values using the names : "sitkUnkown", "sitkUInt8", etc from PixelIDValueEnum above. This function is used to provide the integer values using calls like:

val = GetPixelIDValueFromString("sitkInt32")

If the pixel type has not been instantiated then the sitkUnknown value (-1) will be returned. If the pixel type string is not recognized (i.e. is not in the set of tested names) then the return value is -99. The idea is to provide a warning (via the R package) if this function needs to be updated to match changes to PixelIDValueEnum - i.e. if a new pixel type is added.

◆ GetVectorImageFromImage() [1/2]

template<class TPixelType , unsigned int NImageDimension, unsigned int NLength>

SITKCommon_HIDDEN itk::VectorImage< TPixelType, NImageDimension >::Pointer itk::simple::GetVectorImageFromImage	(	itk::Image< itk::CovariantVector< TPixelType, NLength >, NImageDimension > *	img,
		bool	transferOwnership = `false`
	)

◆ GetVectorImageFromImage() [2/2]

template<class TPixelType , unsigned int NImageDimension, unsigned int NLength>

SITKCommon_HIDDEN itk::VectorImage< TPixelType, NImageDimension >::Pointer itk::simple::GetVectorImageFromImage	(	itk::Image< itk::Vector< TPixelType, NLength >, NImageDimension > *	img,
		bool	transferOwnership = `false`
	)

Referenced by itk::simple::ProcessObject::CastITKToImage().

◆ Gradient()

Image itk::simple::Gradient	(	const Image &	image1,
		bool	useImageSpacing = `true`,
		bool	useImageDirection = `false`
	)

Computes the gradient of an image using directional derivatives.

\ This function directly calls the execute method of GradientImageFilter in order to support a procedural API

See also: itk::simple::GradientImageFilter for the object oriented interface

◆ GradientAnisotropicDiffusion() [1/2]

Image itk::simple::GradientAnisotropicDiffusion	(	const Image &	image1,
		double	timeStep = `0.125`,
		double	conductanceParameter = `3`,
		unsigned int	conductanceScalingUpdateInterval = `1u`,
		uint32_t	numberOfIterations = `5u`
	)

itk::simple::GradientAnisotropicDiffusionImageFilter Procedural Interface

\ This function directly calls the execute method of GradientAnisotropicDiffusionImageFilter in order to support a procedural API

See also: itk::simple::GradientAnisotropicDiffusionImageFilter for the object oriented interface

◆ GradientAnisotropicDiffusion() [2/2]

Image itk::simple::GradientAnisotropicDiffusion	(	Image &&	image1,
		double	timeStep = `0.125`,
		double	conductanceParameter = `3`,
		unsigned int	conductanceScalingUpdateInterval = `1u`,
		uint32_t	numberOfIterations = `5u`
	)

itk::simple::GradientAnisotropicDiffusionImageFilter Procedural Interface

\ This function directly calls the execute method of GradientAnisotropicDiffusionImageFilter in order to support a procedural API

See also: itk::simple::GradientAnisotropicDiffusionImageFilter for the object oriented interface

◆ GradientMagnitude()

Image itk::simple::GradientMagnitude	(	const Image &	image1,
		bool	useImageSpacing = `true`
	)

Computes the gradient magnitude of an image region at each pixel.

\ This function directly calls the execute method of GradientMagnitudeImageFilter in order to support a procedural API

See also: itk::simple::GradientMagnitudeImageFilter for the object oriented interface

◆ GradientMagnitudeRecursiveGaussian() [1/2]

Image itk::simple::GradientMagnitudeRecursiveGaussian	(	const Image &	image1,
		double	sigma = `1.0`,
		bool	normalizeAcrossScale = `false`
	)

Computes the Magnitude of the Gradient of an image by convolution with the first derivative of a Gaussian.

\ This function directly calls the execute method of GradientMagnitudeRecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::GradientMagnitudeRecursiveGaussianImageFilter for the object oriented interface

◆ GradientMagnitudeRecursiveGaussian() [2/2]

Image itk::simple::GradientMagnitudeRecursiveGaussian	(	Image &&	image1,
		double	sigma = `1.0`,
		bool	normalizeAcrossScale = `false`
	)

Computes the Magnitude of the Gradient of an image by convolution with the first derivative of a Gaussian.

\ This function directly calls the execute method of GradientMagnitudeRecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::GradientMagnitudeRecursiveGaussianImageFilter for the object oriented interface

◆ GradientRecursiveGaussian()

Image itk::simple::GradientRecursiveGaussian	(	const Image &	image1,
		double	sigma = `1.0`,
		bool	normalizeAcrossScale = `false`,
		bool	useImageDirection = `false`
	)

Computes the gradient of an image by convolution with the first derivative of a Gaussian.

\ This function directly calls the execute method of GradientRecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::GradientRecursiveGaussianImageFilter for the object oriented interface

◆ GrayscaleConnectedClosing()

Image itk::simple::GrayscaleConnectedClosing	(	const Image &	image1,
		std::vector< uint32_t >	seed = `std::vector< uint32_t >(3, 0)`,
		bool	fullyConnected = `false`
	)

Enhance pixels associated with a dark object (identified by a seed pixel) where the dark object is surrounded by a brighter object.

\ This function directly calls the execute method of GrayscaleConnectedClosingImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleConnectedClosingImageFilter for the object oriented interface

◆ GrayscaleConnectedOpening()

Image itk::simple::GrayscaleConnectedOpening	(	const Image &	image1,
		std::vector< unsigned int >	seed = `std::vector< unsigned int >(3, 0)`,
		bool	fullyConnected = `false`
	)

Enhance pixels associated with a bright object (identified by a seed pixel) where the bright object is surrounded by a darker object.

\ This function directly calls the execute method of GrayscaleConnectedOpeningImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleConnectedOpeningImageFilter for the object oriented interface

◆ GrayscaleDilate()

Image itk::simple::GrayscaleDilate	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`
	)

Grayscale dilation of an image.

\ This function directly calls the execute method of GrayscaleDilateImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleDilateImageFilter for the object oriented interface

◆ GrayscaleErode()

Image itk::simple::GrayscaleErode	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`
	)

Grayscale erosion of an image.

\ This function directly calls the execute method of GrayscaleErodeImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleErodeImageFilter for the object oriented interface

Examples: BufferImportExport.cxx.

◆ GrayscaleFillhole()

Image itk::simple::GrayscaleFillhole	(	const Image &	image1,
		bool	fullyConnected = `false`
	)

Remove local minima not connected to the boundary of the image.

\ This function directly calls the execute method of GrayscaleFillholeImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleFillholeImageFilter for the object oriented interface

◆ GrayscaleGeodesicDilate()

Image itk::simple::GrayscaleGeodesicDilate	(	const Image &	image1,
		const Image &	image2,
		bool	runOneIteration = `false`,
		bool	fullyConnected = `false`
	)

geodesic gray scale dilation of an image

\ This function directly calls the execute method of GrayscaleGeodesicDilateImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleGeodesicDilateImageFilter for the object oriented interface

◆ GrayscaleGeodesicErode()

Image itk::simple::GrayscaleGeodesicErode	(	const Image &	image1,
		const Image &	image2,
		bool	runOneIteration = `false`,
		bool	fullyConnected = `false`
	)

geodesic gray scale erosion of an image

\ This function directly calls the execute method of GrayscaleGeodesicErodeImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleGeodesicErodeImageFilter for the object oriented interface

◆ GrayscaleGrindPeak()

Image itk::simple::GrayscaleGrindPeak	(	const Image &	image1,
		bool	fullyConnected = `false`
	)

Remove local maxima not connected to the boundary of the image.

\ This function directly calls the execute method of GrayscaleGrindPeakImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleGrindPeakImageFilter for the object oriented interface

◆ GrayscaleMorphologicalClosing()

Image itk::simple::GrayscaleMorphologicalClosing	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		bool	safeBorder = `true`
	)

gray scale dilation of an image

\ This function directly calls the execute method of GrayscaleMorphologicalClosingImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleMorphologicalClosingImageFilter for the object oriented interface

◆ GrayscaleMorphologicalOpening()

Image itk::simple::GrayscaleMorphologicalOpening	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		bool	safeBorder = `true`
	)

gray scale dilation of an image

\ This function directly calls the execute method of GrayscaleMorphologicalOpeningImageFilter in order to support a procedural API

See also: itk::simple::GrayscaleMorphologicalOpeningImageFilter for the object oriented interface

◆ Greater() [1/5]

Image itk::simple::Greater	(	const Image &	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of GreaterImageFilter in order to support a procedural API

See also: itk::simple::GreaterImageFilter for the object oriented interface

◆ Greater() [2/5]

Image itk::simple::Greater	(	const Image &	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ Greater() [3/5]

Image itk::simple::Greater	(	double	constant,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ Greater() [4/5]

Image itk::simple::Greater	(	Image &&	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of GreaterImageFilter in order to support a procedural API

See also: itk::simple::GreaterImageFilter for the object oriented interface

◆ Greater() [5/5]

Image itk::simple::Greater	(	Image &&	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ GreaterEqual() [1/5]

Image itk::simple::GreaterEqual	(	const Image &	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of GreaterEqualImageFilter in order to support a procedural API

See also: itk::simple::GreaterEqualImageFilter for the object oriented interface

◆ GreaterEqual() [2/5]

Image itk::simple::GreaterEqual	(	const Image &	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ GreaterEqual() [3/5]

Image itk::simple::GreaterEqual	(	double	constant,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ GreaterEqual() [4/5]

Image itk::simple::GreaterEqual	(	Image &&	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of GreaterEqualImageFilter in order to support a procedural API

See also: itk::simple::GreaterEqualImageFilter for the object oriented interface

◆ GreaterEqual() [5/5]

Image itk::simple::GreaterEqual	(	Image &&	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ GridSource()

Image itk::simple::GridSource	(	PixelIDValueEnum	outputPixelType = `itk::simple::sitkFloat32`,
		std::vector< unsigned int >	size = `std::vector< unsigned int >(3, 64)`,
		std::vector< double >	sigma = `std::vector< double >(3, 0.5)`,
		std::vector< double >	gridSpacing = `std::vector< double >(3, 4.0)`,
		std::vector< double >	gridOffset = `std::vector< double >(3, 0.0)`,
		double	scale = `255.0`,
		std::vector< double >	origin = `std::vector< double >(3, 0.0)`,
		std::vector< double >	spacing = `std::vector< double >(3, 1.0)`,
		std::vector< double >	direction = `std::vector< double >()`
	)

Generate an n-dimensional image of a grid.

This function directly calls the execute method of GridImageSource in order to support a procedural API

See also: itk::simple::GridImageSource for the object oriented interface

◆ HalfHermitianToRealInverseFFT()

Image itk::simple::HalfHermitianToRealInverseFFT	(	const Image &	image1,
		bool	actualXDimensionIsOdd = `false`
	)

Base class for specialized complex-to-real inverse Fast Fourier Transform .

\ This function directly calls the execute method of HalfHermitianToRealInverseFFTImageFilter in order to support a procedural API

See also: itk::simple::HalfHermitianToRealInverseFFTImageFilter for the object oriented interface

◆ Hash()

std::string itk::simple::Hash	(	const Image &	image,
		HashImageFilter::HashFunction	function = `HashImageFilter::SHA1`
	)

◆ HConcave()

Image itk::simple::HConcave	(	const Image &	image1,
		double	height = `2.0`,
		bool	fullyConnected = `false`
	)

Identify local minima whose depth below the baseline is greater than h.

\ This function directly calls the execute method of HConcaveImageFilter in order to support a procedural API

See also: itk::simple::HConcaveImageFilter for the object oriented interface

◆ HConvex()

Image itk::simple::HConvex	(	const Image &	image1,
		double	height = `2.0`,
		bool	fullyConnected = `false`
	)

Identify local maxima whose height above the baseline is greater than h.

\ This function directly calls the execute method of HConvexImageFilter in order to support a procedural API

See also: itk::simple::HConvexImageFilter for the object oriented interface

◆ HistogramMatching()

Image itk::simple::HistogramMatching	(	const Image &	image1,
		const Image &	image2,
		uint32_t	numberOfHistogramLevels = `256u`,
		uint32_t	numberOfMatchPoints = `1u`,
		bool	thresholdAtMeanIntensity = `true`
	)

Normalize the grayscale values for a source image by matching the shape of the source image histogram to a reference histogram.

\ This function directly calls the execute method of HistogramMatchingImageFilter in order to support a procedural API

See also: itk::simple::HistogramMatchingImageFilter for the object oriented interface

◆ HMaxima()

Image itk::simple::HMaxima	(	const Image &	image1,
		double	height = `2.0`
	)

Suppress local maxima whose height above the baseline is less than h.

\ This function directly calls the execute method of HMaximaImageFilter in order to support a procedural API

See also: itk::simple::HMaximaImageFilter for the object oriented interface

◆ HMinima()

Image itk::simple::HMinima	(	const Image &	image1,
		double	height = `2.0`,
		bool	fullyConnected = `false`
	)

Suppress local minima whose depth below the baseline is less than h.

\ This function directly calls the execute method of HMinimaImageFilter in order to support a procedural API

See also: itk::simple::HMinimaImageFilter for the object oriented interface

◆ HuangThreshold() [1/2]

Image itk::simple::HuangThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `128u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Huang Threshold.

\ This function directly calls the execute method of HuangThresholdImageFilter in order to support a procedural API

See also: itk::simple::HuangThresholdImageFilter for the object oriented interface

◆ HuangThreshold() [2/2]

Image itk::simple::HuangThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `128u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Huang Threshold.

\ This function directly calls the execute method of HuangThresholdImageFilter in order to support a procedural API

See also: itk::simple::HuangThresholdImageFilter for the object oriented interface

◆ ImportAsDouble()

Image SITKIO_EXPORT itk::simple::ImportAsDouble	(	double *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsFloat()

Image SITKIO_EXPORT itk::simple::ImportAsFloat	(	float *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsInt16()

Image SITKIO_EXPORT itk::simple::ImportAsInt16	(	int16_t *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsInt32()

Image SITKIO_EXPORT itk::simple::ImportAsInt32	(	int32_t *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsInt64()

Image SITKIO_EXPORT itk::simple::ImportAsInt64	(	int64_t *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsInt8()

Image SITKIO_EXPORT itk::simple::ImportAsInt8	(	int8_t *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsUInt16()

Image SITKIO_EXPORT itk::simple::ImportAsUInt16	(	uint16_t *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsUInt32()

Image SITKIO_EXPORT itk::simple::ImportAsUInt32	(	uint32_t *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsUInt64()

Image SITKIO_EXPORT itk::simple::ImportAsUInt64	(	uint64_t *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ ImportAsUInt8()

Image SITKIO_EXPORT itk::simple::ImportAsUInt8	(	uint8_t *	buffer,
		const std::vector< unsigned int > &	size,
		const std::vector< double > &	spacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	origin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	direction = `std::vector< double >()`,
		unsigned int	numberOfComponents = `1`
	)

◆ IntensityWindowing() [1/2]

Image itk::simple::IntensityWindowing	(	const Image &	image1,
		double	windowMinimum = `0.0`,
		double	windowMaximum = `255.0`,
		double	outputMinimum = `0.0`,
		double	outputMaximum = `255.0`
	)

Applies a linear transformation to the intensity levels of the input Image that are inside a user-defined interval. Values below this interval are mapped to a constant. Values over the interval are mapped to another constant.

\ This function directly calls the execute method of IntensityWindowingImageFilter in order to support a procedural API

See also: itk::simple::IntensityWindowingImageFilter for the object oriented interface

◆ IntensityWindowing() [2/2]

Image itk::simple::IntensityWindowing	(	Image &&	image1,
		double	windowMinimum = `0.0`,
		double	windowMaximum = `255.0`,
		double	outputMinimum = `0.0`,
		double	outputMaximum = `255.0`
	)

Applies a linear transformation to the intensity levels of the input Image that are inside a user-defined interval. Values below this interval are mapped to a constant. Values over the interval are mapped to another constant.

\ This function directly calls the execute method of IntensityWindowingImageFilter in order to support a procedural API

See also: itk::simple::IntensityWindowingImageFilter for the object oriented interface

◆ IntermodesThreshold() [1/2]

Image itk::simple::IntermodesThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Intermodes Threshold.

\ This function directly calls the execute method of IntermodesThresholdImageFilter in order to support a procedural API

See also: itk::simple::IntermodesThresholdImageFilter for the object oriented interface

◆ IntermodesThreshold() [2/2]

Image itk::simple::IntermodesThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Intermodes Threshold.

\ This function directly calls the execute method of IntermodesThresholdImageFilter in order to support a procedural API

See also: itk::simple::IntermodesThresholdImageFilter for the object oriented interface

◆ InverseDeconvolution()

Image itk::simple::InverseDeconvolution	(	const Image &	image1,
		const Image &	image2,
		double	kernelZeroMagnitudeThreshold = `1.0e-4`,
		bool	normalize = `false`,
		InverseDeconvolutionImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::InverseDeconvolutionImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		InverseDeconvolutionImageFilter::OutputRegionModeType	outputRegionMode = `itk::simple::InverseDeconvolutionImageFilter::SAME`
	)

The direct linear inverse deconvolution filter.

\ This function directly calls the execute method of InverseDeconvolutionImageFilter in order to support a procedural API

See also: itk::simple::InverseDeconvolutionImageFilter for the object oriented interface

◆ InverseDisplacementField()

Image itk::simple::InverseDisplacementField	(	const Image &	image1,
		std::vector< uint32_t >	size = `std::vector< uint32_t >(3, 0)`,
		std::vector< double >	outputOrigin = `std::vector< double >(3, 0.0)`,
		std::vector< double >	outputSpacing = `std::vector< double >(3, 1.0)`,
		unsigned int	subsamplingFactor = `16u`
	)

Computes the inverse of a displacement field.

\ This function directly calls the execute method of InverseDisplacementFieldImageFilter in order to support a procedural API

See also: itk::simple::InverseDisplacementFieldImageFilter for the object oriented interface

◆ InverseFFT()

Image itk::simple::InverseFFT ( const Image & image1 )

Base class for inverse Fast Fourier Transform .

\ This function directly calls the execute method of InverseFFTImageFilter in order to support a procedural API

See also: itk::simple::InverseFFTImageFilter for the object oriented interface

◆ InvertDisplacementField()

Image itk::simple::InvertDisplacementField	(	const Image &	image1,
		uint32_t	maximumNumberOfIterations = `10u`,
		double	maxErrorToleranceThreshold = `0.1`,
		double	meanErrorToleranceThreshold = `0.001`,
		bool	enforceBoundaryCondition = `true`
	)

Iteratively estimate the inverse field of a displacement field.

\ This function directly calls the execute method of InvertDisplacementFieldImageFilter in order to support a procedural API

See also: itk::simple::InvertDisplacementFieldImageFilter for the object oriented interface

◆ InvertIntensity() [1/2]

Image itk::simple::InvertIntensity	(	const Image &	image1,
		double	maximum = `255`
	)

Invert the intensity of an image.

\ This function directly calls the execute method of InvertIntensityImageFilter in order to support a procedural API

See also: itk::simple::InvertIntensityImageFilter for the object oriented interface

◆ InvertIntensity() [2/2]

Image itk::simple::InvertIntensity	(	Image &&	image1,
		double	maximum = `255`
	)

Invert the intensity of an image.

\ This function directly calls the execute method of InvertIntensityImageFilter in order to support a procedural API

See also: itk::simple::InvertIntensityImageFilter for the object oriented interface

◆ IsoContourDistance()

Image itk::simple::IsoContourDistance	(	const Image &	image1,
		double	levelSetValue = `0.0`,
		double	farValue = `10`
	)

Compute an approximate distance from an interpolated isocontour to the close grid points.

\ This function directly calls the execute method of IsoContourDistanceImageFilter in order to support a procedural API

See also: itk::simple::IsoContourDistanceImageFilter for the object oriented interface

◆ IsoDataThreshold() [1/2]

Image itk::simple::IsoDataThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the IsoData Threshold.

\ This function directly calls the execute method of IsoDataThresholdImageFilter in order to support a procedural API

See also: itk::simple::IsoDataThresholdImageFilter for the object oriented interface

◆ IsoDataThreshold() [2/2]

Image itk::simple::IsoDataThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the IsoData Threshold.

\ This function directly calls the execute method of IsoDataThresholdImageFilter in order to support a procedural API

See also: itk::simple::IsoDataThresholdImageFilter for the object oriented interface

◆ IsolatedConnected()

Image itk::simple::IsolatedConnected	(	const Image &	image1,
		std::vector< unsigned int >	seed1 = `std::vector< unsigned int >(3, 0)`,
		std::vector< unsigned int >	seed2 = `std::vector< unsigned int >(3, 0)`,
		double	lower = `0`,
		double	upper = `1`,
		uint8_t	replaceValue = `1u`,
		double	isolatedValueTolerance = `1.0`,
		bool	findUpperThreshold = `true`
	)

Label pixels that are connected to one set of seeds but not another.

\ This function directly calls the execute method of IsolatedConnectedImageFilter in order to support a procedural API

See also: itk::simple::IsolatedConnectedImageFilter for the object oriented interface

◆ IsolatedWatershed()

Image itk::simple::IsolatedWatershed	(	const Image &	image1,
		std::vector< uint32_t >	seed1 = `std::vector< uint32_t >(3, 0)`,
		std::vector< uint32_t >	seed2 = `std::vector< uint32_t >(3, 0)`,
		double	threshold = `0.0`,
		double	upperValueLimit = `1.0`,
		double	isolatedValueTolerance = `0.001`,
		uint8_t	replaceValue1 = `1u`,
		uint8_t	replaceValue2 = `2u`
	)

Isolate watershed basins using two seeds.

\ This function directly calls the execute method of IsolatedWatershedImageFilter in order to support a procedural API

See also: itk::simple::IsolatedWatershedImageFilter for the object oriented interface

◆ IterativeInverseDisplacementField()

Image itk::simple::IterativeInverseDisplacementField	(	const Image &	image1,
		uint32_t	numberOfIterations = `5u`,
		double	stopValue = `0.0`
	)

Computes the inverse of a displacement field.

\ This function directly calls the execute method of IterativeInverseDisplacementFieldImageFilter in order to support a procedural API

See also: itk::simple::IterativeInverseDisplacementFieldImageFilter for the object oriented interface

◆ JoinSeries() [1/6]

Image itk::simple::JoinSeries	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5,
		double	origin = `0.0`,
		double	spacing = `1.0`
	)

Join N-D images into an (N+1)-D image.

This function directly calls the execute method of JoinSeriesImageFilter in order to support a procedural API

See also: itk::simple::JoinSeriesImageFilter for the object oriented interface

◆ JoinSeries() [2/6]

Image itk::simple::JoinSeries	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		double	origin = `0.0`,
		double	spacing = `1.0`
	)

Join N-D images into an (N+1)-D image.

This function directly calls the execute method of JoinSeriesImageFilter in order to support a procedural API

See also: itk::simple::JoinSeriesImageFilter for the object oriented interface

◆ JoinSeries() [3/6]

Image itk::simple::JoinSeries	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		double	origin = `0.0`,
		double	spacing = `1.0`
	)

Join N-D images into an (N+1)-D image.

This function directly calls the execute method of JoinSeriesImageFilter in order to support a procedural API

See also: itk::simple::JoinSeriesImageFilter for the object oriented interface

◆ JoinSeries() [4/6]

Image itk::simple::JoinSeries	(	const Image &	image1,
		const Image &	image2,
		double	origin = `0.0`,
		double	spacing = `1.0`
	)

Join N-D images into an (N+1)-D image.

This function directly calls the execute method of JoinSeriesImageFilter in order to support a procedural API

See also: itk::simple::JoinSeriesImageFilter for the object oriented interface

◆ JoinSeries() [5/6]

Image itk::simple::JoinSeries	(	const Image &	image1,
		double	origin = `0.0`,
		double	spacing = `1.0`
	)

Join N-D images into an (N+1)-D image.

This function directly calls the execute method of JoinSeriesImageFilter in order to support a procedural API

See also: itk::simple::JoinSeriesImageFilter for the object oriented interface

◆ JoinSeries() [6/6]

Image itk::simple::JoinSeries	(	const std::vector< Image > &	images,
		double	origin = `0.0`,
		double	spacing = `1.0`
	)

Join N-D images into an (N+1)-D image.

This function directly calls the execute method of JoinSeriesImageFilter in order to support a procedural API

See also: itk::simple::JoinSeriesImageFilter for the object oriented interface

◆ KittlerIllingworthThreshold() [1/2]

Image itk::simple::KittlerIllingworthThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the KittlerIllingworth Threshold.

\ This function directly calls the execute method of KittlerIllingworthThresholdImageFilter in order to support a procedural API

See also: itk::simple::KittlerIllingworthThresholdImageFilter for the object oriented interface

◆ KittlerIllingworthThreshold() [2/2]

Image itk::simple::KittlerIllingworthThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the KittlerIllingworth Threshold.

\ This function directly calls the execute method of KittlerIllingworthThresholdImageFilter in order to support a procedural API

See also: itk::simple::KittlerIllingworthThresholdImageFilter for the object oriented interface

◆ LabelContour() [1/2]

Image itk::simple::LabelContour	(	const Image &	image1,
		bool	fullyConnected = `false`,
		double	backgroundValue = `0`
	)

Labels the pixels on the border of the objects in a labeled image.

\ This function directly calls the execute method of LabelContourImageFilter in order to support a procedural API

See also: itk::simple::LabelContourImageFilter for the object oriented interface

◆ LabelContour() [2/2]

Image itk::simple::LabelContour	(	Image &&	image1,
		bool	fullyConnected = `false`,
		double	backgroundValue = `0`
	)

Labels the pixels on the border of the objects in a labeled image.

\ This function directly calls the execute method of LabelContourImageFilter in order to support a procedural API

See also: itk::simple::LabelContourImageFilter for the object oriented interface

◆ LabelImageToLabelMap()

Image itk::simple::LabelImageToLabelMap	(	const Image &	image1,
		double	backgroundValue = `0`
	)

convert a labeled image to a label collection image

\ This function directly calls the execute method of LabelImageToLabelMapFilter in order to support a procedural API

See also: itk::simple::LabelImageToLabelMapFilter for the object oriented interface

◆ LabelMapContourOverlay()

Image itk::simple::LabelMapContourOverlay	(	const Image &	labelMapImage,
		const Image &	featureImage,
		double	opacity = `0.5`,
		std::vector< unsigned int >	dilationRadius = `std::vector< unsigned int >(3, 1)`,
		std::vector< unsigned int >	contourThickness = `std::vector< unsigned int >(3, 1)`,
		unsigned int	sliceDimension = `0u`,
		LabelMapContourOverlayImageFilter::ContourTypeType	contourType = `itk::simple::LabelMapContourOverlayImageFilter::CONTOUR`,
		LabelMapContourOverlayImageFilter::PriorityType	priority = `itk::simple::LabelMapContourOverlayImageFilter::HIGH_LABEL_ON_TOP`,
		std::vector< uint8_t >	colormap = `std::vector< uint8_t >()`
	)

Apply a colormap to the contours (outlines) of each object in a label map and superimpose it on top of the feature image.

\ This function directly calls the execute method of LabelMapContourOverlayImageFilter in order to support a procedural API

See also: itk::simple::LabelMapContourOverlayImageFilter for the object oriented interface

◆ LabelMapMask()

Image itk::simple::LabelMapMask	(	const Image &	labelMapImage,
		const Image &	featureImage,
		uint64_t	label = `1u`,
		double	backgroundValue = `0`,
		bool	negated = `false`,
		bool	crop = `false`,
		std::vector< unsigned int >	cropBorder = `std::vector< unsigned int >(3, 0)`
	)

Mask and image with a LabelMap .

\ This function directly calls the execute method of LabelMapMaskImageFilter in order to support a procedural API

See also: itk::simple::LabelMapMaskImageFilter for the object oriented interface

◆ LabelMapOverlay()

Image itk::simple::LabelMapOverlay	(	const Image &	labelMapImage,
		const Image &	featureImage,
		double	opacity = `0.5`,
		std::vector< unsigned char >	colormap = `std::vector< unsigned char >()`
	)

Apply a colormap to a label map and superimpose it on an image.

\ This function directly calls the execute method of LabelMapOverlayImageFilter in order to support a procedural API

See also: itk::simple::LabelMapOverlayImageFilter for the object oriented interface

◆ LabelMapToBinary()

Image itk::simple::LabelMapToBinary	(	const Image &	image1,
		double	backgroundValue = `0`,
		double	foregroundValue = `1.0`
	)

Convert a LabelMap to a binary image.

\ This function directly calls the execute method of LabelMapToBinaryImageFilter in order to support a procedural API

See also: itk::simple::LabelMapToBinaryImageFilter for the object oriented interface

◆ LabelMapToLabel()

Image itk::simple::LabelMapToLabel ( const Image & image1 )

Converts a LabelMap to a labeled image.

\ This function directly calls the execute method of LabelMapToLabelImageFilter in order to support a procedural API

See also: itk::simple::LabelMapToLabelImageFilter for the object oriented interface

◆ LabelMapToRGB()

Image itk::simple::LabelMapToRGB	(	const Image &	image1,
		std::vector< uint8_t >	colormap = `std::vector< uint8_t >()`
	)

Convert a LabelMap to a colored image.

\ This function directly calls the execute method of LabelMapToRGBImageFilter in order to support a procedural API

See also: itk::simple::LabelMapToRGBImageFilter for the object oriented interface

◆ LabelOverlay() [1/2]

Image itk::simple::LabelOverlay	(	const Image &	image,
		const Image &	labelImage,
		double	opacity = `0.5`,
		double	backgroundValue = `0.0`,
		std::vector< uint8_t >	colormap = `std::vector< uint8_t >()`
	)

Apply a colormap to a label image and put it on top of the input image.

\ This function directly calls the execute method of LabelOverlayImageFilter in order to support a procedural API

See also: itk::simple::LabelOverlayImageFilter for the object oriented interface

◆ LabelOverlay() [2/2]

Image itk::simple::LabelOverlay	(	Image &&	image,
		const Image &	labelImage,
		double	opacity = `0.5`,
		double	backgroundValue = `0.0`,
		std::vector< uint8_t >	colormap = `std::vector< uint8_t >()`
	)

Apply a colormap to a label image and put it on top of the input image.

\ This function directly calls the execute method of LabelOverlayImageFilter in order to support a procedural API

See also: itk::simple::LabelOverlayImageFilter for the object oriented interface

◆ LabelToRGB() [1/2]

Image itk::simple::LabelToRGB	(	const Image &	image1,
		double	backgroundValue = `0.0`,
		std::vector< uint8_t >	colormap = `std::vector< uint8_t >()`
	)

Apply a colormap to a label image.

\ This function directly calls the execute method of LabelToRGBImageFilter in order to support a procedural API

See also: itk::simple::LabelToRGBImageFilter for the object oriented interface

◆ LabelToRGB() [2/2]

Image itk::simple::LabelToRGB	(	Image &&	image1,
		double	backgroundValue = `0.0`,
		std::vector< uint8_t >	colormap = `std::vector< uint8_t >()`
	)

Apply a colormap to a label image.

\ This function directly calls the execute method of LabelToRGBImageFilter in order to support a procedural API

See also: itk::simple::LabelToRGBImageFilter for the object oriented interface

◆ LabelUniqueLabelMap() [1/2]

Image itk::simple::LabelUniqueLabelMap	(	const Image &	image1,
		bool	reverseOrdering = `false`
	)

Make sure that the objects are not overlapping.

\ This function directly calls the execute method of LabelUniqueLabelMapFilter in order to support a procedural API

See also: itk::simple::LabelUniqueLabelMapFilter for the object oriented interface

◆ LabelUniqueLabelMap() [2/2]

Image itk::simple::LabelUniqueLabelMap	(	Image &&	image1,
		bool	reverseOrdering = `false`
	)

Make sure that the objects are not overlapping.

\ This function directly calls the execute method of LabelUniqueLabelMapFilter in order to support a procedural API

See also: itk::simple::LabelUniqueLabelMapFilter for the object oriented interface

◆ LabelVoting() [1/6]

Image itk::simple::LabelVoting	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`
	)

This filter performs pixelwise voting among an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of LabelVotingImageFilter in order to support a procedural API

See also: itk::simple::LabelVotingImageFilter for the object oriented interface

◆ LabelVoting() [2/6]

Image itk::simple::LabelVoting	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`
	)

This filter performs pixelwise voting among an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of LabelVotingImageFilter in order to support a procedural API

See also: itk::simple::LabelVotingImageFilter for the object oriented interface

◆ LabelVoting() [3/6]

Image itk::simple::LabelVoting	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`
	)

This filter performs pixelwise voting among an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of LabelVotingImageFilter in order to support a procedural API

See also: itk::simple::LabelVotingImageFilter for the object oriented interface

◆ LabelVoting() [4/6]

Image itk::simple::LabelVoting	(	const Image &	image1,
		const Image &	image2,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`
	)

This filter performs pixelwise voting among an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of LabelVotingImageFilter in order to support a procedural API

See also: itk::simple::LabelVotingImageFilter for the object oriented interface

◆ LabelVoting() [5/6]

Image itk::simple::LabelVoting	(	const Image &	image1,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`
	)

This filter performs pixelwise voting among an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of LabelVotingImageFilter in order to support a procedural API

See also: itk::simple::LabelVotingImageFilter for the object oriented interface

◆ LabelVoting() [6/6]

Image itk::simple::LabelVoting	(	const std::vector< Image > &	images,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`
	)

This filter performs pixelwise voting among an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of LabelVotingImageFilter in order to support a procedural API

See also: itk::simple::LabelVotingImageFilter for the object oriented interface

◆ LandmarkBasedTransformInitializer()

Transform itk::simple::LandmarkBasedTransformInitializer	(	const Transform &	transform,
		const std::vector< double > &	fixedLandmarks = `std::vector< double >()`,
		const std::vector< double > &	movingLandmarks = `std::vector< double >()`,
		const std::vector< double > &	landmarkWeight = `std::vector< double >()`,
		const Image &	referenceImage = `Image()`,
		unsigned int	numberOfControlPoints = `4u`
	)

itk::simple::LandmarkBasedTransformInitializerFilter Procedural Interface

This function directly calls the execute method of LandmarkBasedTransformInitializerFilter in order to support a procedural API

See also: itk::simple::LandmarkBasedTransformInitializerFilter for the object oriented interface

◆ LandweberDeconvolution()

Image itk::simple::LandweberDeconvolution	(	const Image &	image1,
		const Image &	image2,
		double	alpha = `0.1`,
		int	numberOfIterations = `1`,
		bool	normalize = `false`,
		LandweberDeconvolutionImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::LandweberDeconvolutionImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		LandweberDeconvolutionImageFilter::OutputRegionModeType	outputRegionMode = `itk::simple::LandweberDeconvolutionImageFilter::SAME`
	)

Deconvolve an image using the Landweber deconvolution algorithm.

\ This function directly calls the execute method of LandweberDeconvolutionImageFilter in order to support a procedural API

See also: itk::simple::LandweberDeconvolutionImageFilter for the object oriented interface

◆ Laplacian()

Image itk::simple::Laplacian	(	const Image &	image1,
		bool	useImageSpacing = `true`
	)

itk::simple::LaplacianImageFilter Procedural Interface

\ This function directly calls the execute method of LaplacianImageFilter in order to support a procedural API

See also: itk::simple::LaplacianImageFilter for the object oriented interface

◆ LaplacianRecursiveGaussian()

Image itk::simple::LaplacianRecursiveGaussian	(	const Image &	image1,
		double	sigma = `1.0`,
		bool	normalizeAcrossScale = `false`
	)

Computes the Laplacian of Gaussian (LoG) of an image.

\ This function directly calls the execute method of LaplacianRecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::LaplacianRecursiveGaussianImageFilter for the object oriented interface

◆ LaplacianSegmentationLevelSet() [1/2]

Image itk::simple::LaplacianSegmentationLevelSet	(	const Image &	initialImage,
		const Image &	featureImage,
		double	maximumRMSError = `0.02`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`
	)

Segments structures in images based on a second derivative image features.

\ This function directly calls the execute method of LaplacianSegmentationLevelSetImageFilter in order to support a procedural API

See also: itk::simple::LaplacianSegmentationLevelSetImageFilter for the object oriented interface

◆ LaplacianSegmentationLevelSet() [2/2]

Image itk::simple::LaplacianSegmentationLevelSet	(	Image &&	initialImage,
		const Image &	featureImage,
		double	maximumRMSError = `0.02`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`
	)

Segments structures in images based on a second derivative image features.

\ This function directly calls the execute method of LaplacianSegmentationLevelSetImageFilter in order to support a procedural API

See also: itk::simple::LaplacianSegmentationLevelSetImageFilter for the object oriented interface

◆ LaplacianSharpening()

Image itk::simple::LaplacianSharpening	(	const Image &	image1,
		bool	useImageSpacing = `true`
	)

This filter sharpens an image using a Laplacian. LaplacianSharpening highlights regions of rapid intensity change and therefore highlights or enhances the edges. The result is an image that appears more in focus.

\ This function directly calls the execute method of LaplacianSharpeningImageFilter in order to support a procedural API

See also: itk::simple::LaplacianSharpeningImageFilter for the object oriented interface

◆ Less() [1/5]

Image itk::simple::Less	(	const Image &	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of LessImageFilter in order to support a procedural API

See also: itk::simple::LessImageFilter for the object oriented interface

◆ Less() [2/5]

Image itk::simple::Less	(	const Image &	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ Less() [3/5]

Image itk::simple::Less	(	double	constant,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ Less() [4/5]

Image itk::simple::Less	(	Image &&	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of LessImageFilter in order to support a procedural API

See also: itk::simple::LessImageFilter for the object oriented interface

◆ Less() [5/5]

Image itk::simple::Less	(	Image &&	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ LessEqual() [1/5]

Image itk::simple::LessEqual	(	const Image &	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of LessEqualImageFilter in order to support a procedural API

See also: itk::simple::LessEqualImageFilter for the object oriented interface

◆ LessEqual() [2/5]

Image itk::simple::LessEqual	(	const Image &	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ LessEqual() [3/5]

Image itk::simple::LessEqual	(	double	constant,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ LessEqual() [4/5]

Image itk::simple::LessEqual	(	Image &&	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of LessEqualImageFilter in order to support a procedural API

See also: itk::simple::LessEqualImageFilter for the object oriented interface

◆ LessEqual() [5/5]

Image itk::simple::LessEqual	(	Image &&	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ LiThreshold() [1/2]

Image itk::simple::LiThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Li Threshold.

\ This function directly calls the execute method of LiThresholdImageFilter in order to support a procedural API

See also: itk::simple::LiThresholdImageFilter for the object oriented interface

◆ LiThreshold() [2/2]

Image itk::simple::LiThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Li Threshold.

\ This function directly calls the execute method of LiThresholdImageFilter in order to support a procedural API

See also: itk::simple::LiThresholdImageFilter for the object oriented interface

◆ Log() [1/2]

Image itk::simple::Log ( const Image & image1 )

Computes the log() of each pixel.

\ This function directly calls the execute method of LogImageFilter in order to support a procedural API

See also: itk::simple::LogImageFilter for the object oriented interface

◆ Log() [2/2]

Image itk::simple::Log ( Image && image1 )

Computes the log() of each pixel.

\ This function directly calls the execute method of LogImageFilter in order to support a procedural API

See also: itk::simple::LogImageFilter for the object oriented interface

◆ Log10() [1/2]

Image itk::simple::Log10 ( const Image & image1 )

Computes the log10 of each pixel.

\ This function directly calls the execute method of Log10ImageFilter in order to support a procedural API

See also: itk::simple::Log10ImageFilter for the object oriented interface

◆ Log10() [2/2]

Image itk::simple::Log10 ( Image && image1 )

Computes the log10 of each pixel.

\ This function directly calls the execute method of Log10ImageFilter in order to support a procedural API

See also: itk::simple::Log10ImageFilter for the object oriented interface

◆ MagnitudeAndPhaseToComplex() [1/5]

Image itk::simple::MagnitudeAndPhaseToComplex	(	const Image &	image1,
		const Image &	image2
	)

Implements pixel-wise conversion of magnitude and phase data into complex voxels.

\ This function directly calls the execute method of MagnitudeAndPhaseToComplexImageFilter in order to support a procedural API

See also: itk::simple::MagnitudeAndPhaseToComplexImageFilter for the object oriented interface

◆ MagnitudeAndPhaseToComplex() [2/5]

Image itk::simple::MagnitudeAndPhaseToComplex	(	const Image &	image1,
		double	constant
	)

◆ MagnitudeAndPhaseToComplex() [3/5]

Image itk::simple::MagnitudeAndPhaseToComplex	(	double	constant,
		const Image &	image2
	)

◆ MagnitudeAndPhaseToComplex() [4/5]

Image itk::simple::MagnitudeAndPhaseToComplex	(	Image &&	image1,
		const Image &	image2
	)

Implements pixel-wise conversion of magnitude and phase data into complex voxels.

\ This function directly calls the execute method of MagnitudeAndPhaseToComplexImageFilter in order to support a procedural API

See also: itk::simple::MagnitudeAndPhaseToComplexImageFilter for the object oriented interface

◆ MagnitudeAndPhaseToComplex() [5/5]

Image itk::simple::MagnitudeAndPhaseToComplex	(	Image &&	image1,
		double	constant
	)

◆ make_scope_exit()

template<typename F >

scope_exit<F> itk::simple::make_scope_exit ( F && f )

noexcept

Definition at line 253 of file sitkTemplateFunctions.h.

◆ Mask() [1/2]

Image itk::simple::Mask	(	const Image &	image,
		const Image &	maskImage,
		double	outsideValue = `0`,
		double	maskingValue = `0`
	)

Mask an image with a mask.

\ This function directly calls the execute method of MaskImageFilter in order to support a procedural API

See also: itk::simple::MaskImageFilter for the object oriented interface

◆ Mask() [2/2]

Image itk::simple::Mask	(	Image &&	image,
		const Image &	maskImage,
		double	outsideValue = `0`,
		double	maskingValue = `0`
	)

Mask an image with a mask.

\ This function directly calls the execute method of MaskImageFilter in order to support a procedural API

See also: itk::simple::MaskImageFilter for the object oriented interface

◆ MaskedFFTNormalizedCorrelation()

Image itk::simple::MaskedFFTNormalizedCorrelation	(	const Image &	fixedImage,
		const Image &	movingImage,
		const Image &	fixedImageMask,
		const Image &	movingImageMask,
		uint64_t	requiredNumberOfOverlappingPixels = `0u`,
		float	requiredFractionOfOverlappingPixels = `0.0`
	)

Calculate masked normalized cross correlation using FFTs.

\ This function directly calls the execute method of MaskedFFTNormalizedCorrelationImageFilter in order to support a procedural API

See also: itk::simple::MaskedFFTNormalizedCorrelationImageFilter for the object oriented interface

◆ MaskNegated() [1/2]

Image itk::simple::MaskNegated	(	const Image &	image,
		const Image &	maskImage,
		double	outsideValue = `0`,
		double	maskingValue = `0`
	)

Mask an image with the negation (or logical compliment) of a mask.

\ This function directly calls the execute method of MaskNegatedImageFilter in order to support a procedural API

See also: itk::simple::MaskNegatedImageFilter for the object oriented interface

◆ MaskNegated() [2/2]

Image itk::simple::MaskNegated	(	Image &&	image,
		const Image &	maskImage,
		double	outsideValue = `0`,
		double	maskingValue = `0`
	)

Mask an image with the negation (or logical compliment) of a mask.

\ This function directly calls the execute method of MaskNegatedImageFilter in order to support a procedural API

See also: itk::simple::MaskNegatedImageFilter for the object oriented interface

◆ Maximum() [1/5]

Image itk::simple::Maximum	(	const Image &	image1,
		const Image &	image2
	)

Implements a pixel-wise operator Max(a,b) between two images.

\ This function directly calls the execute method of MaximumImageFilter in order to support a procedural API

See also: itk::simple::MaximumImageFilter for the object oriented interface

◆ Maximum() [2/5]

Image itk::simple::Maximum	(	const Image &	image1,
		double	constant
	)

◆ Maximum() [3/5]

Image itk::simple::Maximum	(	double	constant,
		const Image &	image2
	)

◆ Maximum() [4/5]

Image itk::simple::Maximum	(	Image &&	image1,
		const Image &	image2
	)

Implements a pixel-wise operator Max(a,b) between two images.

\ This function directly calls the execute method of MaximumImageFilter in order to support a procedural API

See also: itk::simple::MaximumImageFilter for the object oriented interface

Referenced by itk::simple::InvertIntensityImageFilter::SetMaximum().

◆ Maximum() [5/5]

Image itk::simple::Maximum	(	Image &&	image1,
		double	constant
	)

◆ MaximumEntropyThreshold() [1/2]

Image itk::simple::MaximumEntropyThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the MaximumEntropy Threshold.

\ This function directly calls the execute method of MaximumEntropyThresholdImageFilter in order to support a procedural API

See also: itk::simple::MaximumEntropyThresholdImageFilter for the object oriented interface

◆ MaximumEntropyThreshold() [2/2]

Image itk::simple::MaximumEntropyThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the MaximumEntropy Threshold.

\ This function directly calls the execute method of MaximumEntropyThresholdImageFilter in order to support a procedural API

See also: itk::simple::MaximumEntropyThresholdImageFilter for the object oriented interface

◆ MaximumProjection()

Image itk::simple::MaximumProjection	(	const Image &	image1,
		unsigned int	projectionDimension = `0u`
	)

Maximum projection.

\ This function directly calls the execute method of MaximumProjectionImageFilter in order to support a procedural API

See also: itk::simple::MaximumProjectionImageFilter for the object oriented interface

◆ Mean()

Image itk::simple::Mean	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`
	)

Applies an averaging filter to an image.

\ This function directly calls the execute method of MeanImageFilter in order to support a procedural API

See also: itk::simple::MeanImageFilter for the object oriented interface

Referenced by itk::simple::AdditiveGaussianNoiseImageFilter::SetMean(), itk::simple::GaussianImageSource::SetMean(), and itk::simple::GaborImageSource::SetMean().

◆ MeanProjection()

Image itk::simple::MeanProjection	(	const Image &	image1,
		unsigned int	projectionDimension = `0u`
	)

Mean projection.

\ This function directly calls the execute method of MeanProjectionImageFilter in order to support a procedural API

See also: itk::simple::MeanProjectionImageFilter for the object oriented interface

◆ Median()

Image itk::simple::Median	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`
	)

Applies a median filter to an image.

\ This function directly calls the execute method of MedianImageFilter in order to support a procedural API

See also: itk::simple::MedianImageFilter for the object oriented interface

◆ MedianProjection()

Image itk::simple::MedianProjection	(	const Image &	image1,
		unsigned int	projectionDimension = `0u`
	)

Median projection.

\ This function directly calls the execute method of MedianProjectionImageFilter in order to support a procedural API

See also: itk::simple::MedianProjectionImageFilter for the object oriented interface

◆ MergeLabelMap() [1/6]

Image itk::simple::MergeLabelMap	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5,
		MergeLabelMapFilter::MethodType	method = `itk::simple::MergeLabelMapFilter::Keep`
	)

Merges several Label Maps.

This function directly calls the execute method of MergeLabelMapFilter in order to support a procedural API

See also: itk::simple::MergeLabelMapFilter for the object oriented interface

◆ MergeLabelMap() [2/6]

Image itk::simple::MergeLabelMap	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		MergeLabelMapFilter::MethodType	method = `itk::simple::MergeLabelMapFilter::Keep`
	)

Merges several Label Maps.

This function directly calls the execute method of MergeLabelMapFilter in order to support a procedural API

See also: itk::simple::MergeLabelMapFilter for the object oriented interface

◆ MergeLabelMap() [3/6]

Image itk::simple::MergeLabelMap	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		MergeLabelMapFilter::MethodType	method = `itk::simple::MergeLabelMapFilter::Keep`
	)

Merges several Label Maps.

This function directly calls the execute method of MergeLabelMapFilter in order to support a procedural API

See also: itk::simple::MergeLabelMapFilter for the object oriented interface

◆ MergeLabelMap() [4/6]

Image itk::simple::MergeLabelMap	(	const Image &	image1,
		const Image &	image2,
		MergeLabelMapFilter::MethodType	method = `itk::simple::MergeLabelMapFilter::Keep`
	)

Merges several Label Maps.

This function directly calls the execute method of MergeLabelMapFilter in order to support a procedural API

See also: itk::simple::MergeLabelMapFilter for the object oriented interface

◆ MergeLabelMap() [5/6]

Image itk::simple::MergeLabelMap	(	const Image &	image1,
		MergeLabelMapFilter::MethodType	method = `itk::simple::MergeLabelMapFilter::Keep`
	)

Merges several Label Maps.

This function directly calls the execute method of MergeLabelMapFilter in order to support a procedural API

See also: itk::simple::MergeLabelMapFilter for the object oriented interface

◆ MergeLabelMap() [6/6]

Image itk::simple::MergeLabelMap	(	const std::vector< Image > &	images,
		MergeLabelMapFilter::MethodType	method = `itk::simple::MergeLabelMapFilter::Keep`
	)

Merges several Label Maps.

This function directly calls the execute method of MergeLabelMapFilter in order to support a procedural API

See also: itk::simple::MergeLabelMapFilter for the object oriented interface

◆ Minimum() [1/5]

Image itk::simple::Minimum	(	const Image &	image1,
		const Image &	image2
	)

Implements a pixel-wise operator Min(a,b) between two images.

\ This function directly calls the execute method of MinimumImageFilter in order to support a procedural API

See also: itk::simple::MinimumImageFilter for the object oriented interface

◆ Minimum() [2/5]

Image itk::simple::Minimum	(	const Image &	image1,
		double	constant
	)

◆ Minimum() [3/5]

Image itk::simple::Minimum	(	double	constant,
		const Image &	image2
	)

◆ Minimum() [4/5]

Image itk::simple::Minimum	(	Image &&	image1,
		const Image &	image2
	)

Implements a pixel-wise operator Min(a,b) between two images.

\ This function directly calls the execute method of MinimumImageFilter in order to support a procedural API

See also: itk::simple::MinimumImageFilter for the object oriented interface

◆ Minimum() [5/5]

Image itk::simple::Minimum	(	Image &&	image1,
		double	constant
	)

◆ MinimumProjection()

Image itk::simple::MinimumProjection	(	const Image &	image1,
		unsigned int	projectionDimension = `0u`
	)

Minimum projection.

\ This function directly calls the execute method of MinimumProjectionImageFilter in order to support a procedural API

See also: itk::simple::MinimumProjectionImageFilter for the object oriented interface

◆ MinMaxCurvatureFlow() [1/2]

Image itk::simple::MinMaxCurvatureFlow	(	const Image &	image1,
		double	timeStep = `0.05`,
		uint32_t	numberOfIterations = `5u`,
		int	stencilRadius = `2`
	)

Denoise an image using min/max curvature flow.

\ This function directly calls the execute method of MinMaxCurvatureFlowImageFilter in order to support a procedural API

See also: itk::simple::MinMaxCurvatureFlowImageFilter for the object oriented interface

◆ MinMaxCurvatureFlow() [2/2]

Image itk::simple::MinMaxCurvatureFlow	(	Image &&	image1,
		double	timeStep = `0.05`,
		uint32_t	numberOfIterations = `5u`,
		int	stencilRadius = `2`
	)

Denoise an image using min/max curvature flow.

\ This function directly calls the execute method of MinMaxCurvatureFlowImageFilter in order to support a procedural API

See also: itk::simple::MinMaxCurvatureFlowImageFilter for the object oriented interface

◆ MirrorPad()

Image itk::simple::MirrorPad	(	const Image &	image1,
		std::vector< unsigned int >	padLowerBound = `std::vector< unsigned int >(3, 0)`,
		std::vector< unsigned int >	padUpperBound = `std::vector< unsigned int >(3, 0)`,
		double	decayBase = `1.0`
	)

Increase the image size by padding with replicants of the input image value.

\ This function directly calls the execute method of MirrorPadImageFilter in order to support a procedural API

See also: itk::simple::MirrorPadImageFilter for the object oriented interface

◆ Modulus() [1/5]

Image itk::simple::Modulus	(	const Image &	image1,
		const Image &	image2
	)

Computes the modulus (x % dividend) pixel-wise.

\ This function directly calls the execute method of ModulusImageFilter in order to support a procedural API

See also: itk::simple::ModulusImageFilter for the object oriented interface

◆ Modulus() [2/5]

Image itk::simple::Modulus	(	const Image &	image1,
		uint32_t	constant
	)

◆ Modulus() [3/5]

Image itk::simple::Modulus	(	Image &&	image1,
		const Image &	image2
	)

Computes the modulus (x % dividend) pixel-wise.

\ This function directly calls the execute method of ModulusImageFilter in order to support a procedural API

See also: itk::simple::ModulusImageFilter for the object oriented interface

Referenced by operator%(), and operator%=().

◆ Modulus() [4/5]

Image itk::simple::Modulus	(	Image &&	image1,
		uint32_t	constant
	)

◆ Modulus() [5/5]

Image itk::simple::Modulus	(	uint32_t	constant,
		const Image &	image2
	)

◆ MomentsThreshold() [1/2]

Image itk::simple::MomentsThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Moments Threshold.

\ This function directly calls the execute method of MomentsThresholdImageFilter in order to support a procedural API

See also: itk::simple::MomentsThresholdImageFilter for the object oriented interface

◆ MomentsThreshold() [2/2]

Image itk::simple::MomentsThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Moments Threshold.

\ This function directly calls the execute method of MomentsThresholdImageFilter in order to support a procedural API

See also: itk::simple::MomentsThresholdImageFilter for the object oriented interface

◆ MorphologicalGradient()

Image itk::simple::MorphologicalGradient	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`
	)

gray scale dilation of an image

\ This function directly calls the execute method of MorphologicalGradientImageFilter in order to support a procedural API

See also: itk::simple::MorphologicalGradientImageFilter for the object oriented interface

◆ MorphologicalWatershed()

Image itk::simple::MorphologicalWatershed	(	const Image &	image1,
		double	level = `0.0`,
		bool	markWatershedLine = `true`,
		bool	fullyConnected = `false`
	)

Watershed segmentation implementation with morphological operators.

\ This function directly calls the execute method of MorphologicalWatershedImageFilter in order to support a procedural API

See also: itk::simple::MorphologicalWatershedImageFilter for the object oriented interface

◆ MorphologicalWatershedFromMarkers()

Image itk::simple::MorphologicalWatershedFromMarkers	(	const Image &	image,
		const Image &	markerImage,
		bool	markWatershedLine = `true`,
		bool	fullyConnected = `false`
	)

Morphological watershed transform from markers.

\ This function directly calls the execute method of MorphologicalWatershedFromMarkersImageFilter in order to support a procedural API

See also: itk::simple::MorphologicalWatershedFromMarkersImageFilter for the object oriented interface

◆ MultiLabelSTAPLE() [1/6]

Image itk::simple::MultiLabelSTAPLE	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`,
		float	terminationUpdateThreshold = `1e-5f`,
		unsigned int	maximumNumberOfIterations = `std::numeric_limits< unsigned int >::max()`,
		std::vector< float >	priorProbabilities = `std::vector< float >()`
	)

This filter performs a pixelwise combination of an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of MultiLabelSTAPLEImageFilter in order to support a procedural API

See also: itk::simple::MultiLabelSTAPLEImageFilter for the object oriented interface

◆ MultiLabelSTAPLE() [2/6]

Image itk::simple::MultiLabelSTAPLE	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`,
		float	terminationUpdateThreshold = `1e-5f`,
		unsigned int	maximumNumberOfIterations = `std::numeric_limits< unsigned int >::max()`,
		std::vector< float >	priorProbabilities = `std::vector< float >()`
	)

This filter performs a pixelwise combination of an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of MultiLabelSTAPLEImageFilter in order to support a procedural API

See also: itk::simple::MultiLabelSTAPLEImageFilter for the object oriented interface

◆ MultiLabelSTAPLE() [3/6]

Image itk::simple::MultiLabelSTAPLE	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`,
		float	terminationUpdateThreshold = `1e-5f`,
		unsigned int	maximumNumberOfIterations = `std::numeric_limits< unsigned int >::max()`,
		std::vector< float >	priorProbabilities = `std::vector< float >()`
	)

This filter performs a pixelwise combination of an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of MultiLabelSTAPLEImageFilter in order to support a procedural API

See also: itk::simple::MultiLabelSTAPLEImageFilter for the object oriented interface

◆ MultiLabelSTAPLE() [4/6]

Image itk::simple::MultiLabelSTAPLE	(	const Image &	image1,
		const Image &	image2,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`,
		float	terminationUpdateThreshold = `1e-5f`,
		unsigned int	maximumNumberOfIterations = `std::numeric_limits< unsigned int >::max()`,
		std::vector< float >	priorProbabilities = `std::vector< float >()`
	)

This filter performs a pixelwise combination of an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of MultiLabelSTAPLEImageFilter in order to support a procedural API

See also: itk::simple::MultiLabelSTAPLEImageFilter for the object oriented interface

◆ MultiLabelSTAPLE() [5/6]

Image itk::simple::MultiLabelSTAPLE	(	const Image &	image1,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`,
		float	terminationUpdateThreshold = `1e-5f`,
		unsigned int	maximumNumberOfIterations = `std::numeric_limits< unsigned int >::max()`,
		std::vector< float >	priorProbabilities = `std::vector< float >()`
	)

This filter performs a pixelwise combination of an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of MultiLabelSTAPLEImageFilter in order to support a procedural API

See also: itk::simple::MultiLabelSTAPLEImageFilter for the object oriented interface

◆ MultiLabelSTAPLE() [6/6]

Image itk::simple::MultiLabelSTAPLE	(	const std::vector< Image > &	images,
		uint64_t	labelForUndecidedPixels = `std::numeric_limits< uint64_t >::max()`,
		float	terminationUpdateThreshold = `1e-5f`,
		unsigned int	maximumNumberOfIterations = `std::numeric_limits< unsigned int >::max()`,
		std::vector< float >	priorProbabilities = `std::vector< float >()`
	)

This filter performs a pixelwise combination of an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).

This function directly calls the execute method of MultiLabelSTAPLEImageFilter in order to support a procedural API

See also: itk::simple::MultiLabelSTAPLEImageFilter for the object oriented interface

◆ Multiply() [1/5]

Image itk::simple::Multiply	(	const Image &	image1,
		const Image &	image2
	)

Pixel-wise multiplication of two images.

\ This function directly calls the execute method of MultiplyImageFilter in order to support a procedural API

See also: itk::simple::MultiplyImageFilter for the object oriented interface

◆ Multiply() [2/5]

Image itk::simple::Multiply	(	const Image &	image1,
		double	constant
	)

◆ Multiply() [3/5]

Image itk::simple::Multiply	(	double	constant,
		const Image &	image2
	)

◆ Multiply() [4/5]

Image itk::simple::Multiply	(	Image &&	image1,
		const Image &	image2
	)

Pixel-wise multiplication of two images.

\ This function directly calls the execute method of MultiplyImageFilter in order to support a procedural API

See also: itk::simple::MultiplyImageFilter for the object oriented interface

Referenced by operator*(), and operator*=().

◆ Multiply() [5/5]

Image itk::simple::Multiply	(	Image &&	image1,
		double	constant
	)

◆ N4BiasFieldCorrection() [1/2]

Image itk::simple::N4BiasFieldCorrection	(	const Image &	image,
		const Image &	maskImage,
		double	convergenceThreshold = `0.001`,
		std::vector< uint32_t >	maximumNumberOfIterations = `std::vector< uint32_t >(4, 50)`,
		double	biasFieldFullWidthAtHalfMaximum = `0.15`,
		double	wienerFilterNoise = `0.01`,
		uint32_t	numberOfHistogramBins = `200u`,
		std::vector< uint32_t >	numberOfControlPoints = `std::vector< uint32_t >(3, 4)`,
		uint32_t	splineOrder = `3u`,
		bool	useMaskLabel = `true`,
		uint8_t	maskLabel = `1`
	)

Implementation of the N4 bias field correction algorithm.

\ This function directly calls the execute method of N4BiasFieldCorrectionImageFilter in order to support a procedural API

See also: itk::simple::N4BiasFieldCorrectionImageFilter for the object oriented interface

◆ N4BiasFieldCorrection() [2/2]

Image itk::simple::N4BiasFieldCorrection	(	const Image &	image,
		double	convergenceThreshold = `0.001`,
		std::vector< uint32_t >	maximumNumberOfIterations = `std::vector< uint32_t >(4, 50)`,
		double	biasFieldFullWidthAtHalfMaximum = `0.15`,
		double	wienerFilterNoise = `0.01`,
		uint32_t	numberOfHistogramBins = `200u`,
		std::vector< uint32_t >	numberOfControlPoints = `std::vector< uint32_t >(3, 4)`,
		uint32_t	splineOrder = `3u`,
		bool	useMaskLabel = `true`,
		uint8_t	maskLabel = `1`
	)

Implementation of the N4 bias field correction algorithm.

\ This function directly calls the execute method of N4BiasFieldCorrectionImageFilter in order to support a procedural API

See also: itk::simple::N4BiasFieldCorrectionImageFilter for the object oriented interface

◆ NaryAdd() [1/6]

Image itk::simple::NaryAdd ( const Image & image1 )

Pixel-wise addition of N images.

This function directly calls the execute method of NaryAddImageFilter in order to support a procedural API

See also: itk::simple::NaryAddImageFilter for the object oriented interface

◆ NaryAdd() [2/6]

Image itk::simple::NaryAdd	(	const Image &	image1,
		const Image &	image2
	)

Pixel-wise addition of N images.

This function directly calls the execute method of NaryAddImageFilter in order to support a procedural API

See also: itk::simple::NaryAddImageFilter for the object oriented interface

◆ NaryAdd() [3/6]

Image itk::simple::NaryAdd	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3
	)

Pixel-wise addition of N images.

This function directly calls the execute method of NaryAddImageFilter in order to support a procedural API

See also: itk::simple::NaryAddImageFilter for the object oriented interface

◆ NaryAdd() [4/6]

Image itk::simple::NaryAdd	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4
	)

Pixel-wise addition of N images.

This function directly calls the execute method of NaryAddImageFilter in order to support a procedural API

See also: itk::simple::NaryAddImageFilter for the object oriented interface

◆ NaryAdd() [5/6]

Image itk::simple::NaryAdd	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5
	)

Pixel-wise addition of N images.

This function directly calls the execute method of NaryAddImageFilter in order to support a procedural API

See also: itk::simple::NaryAddImageFilter for the object oriented interface

◆ NaryAdd() [6/6]

Image itk::simple::NaryAdd ( const std::vector< Image > & images )

Pixel-wise addition of N images.

This function directly calls the execute method of NaryAddImageFilter in order to support a procedural API

See also: itk::simple::NaryAddImageFilter for the object oriented interface

◆ NaryMaximum() [1/6]

Image itk::simple::NaryMaximum ( const Image & image1 )

Computes the pixel-wise maximum of several images.

This function directly calls the execute method of NaryMaximumImageFilter in order to support a procedural API

See also: itk::simple::NaryMaximumImageFilter for the object oriented interface

◆ NaryMaximum() [2/6]

Image itk::simple::NaryMaximum	(	const Image &	image1,
		const Image &	image2
	)

Computes the pixel-wise maximum of several images.

This function directly calls the execute method of NaryMaximumImageFilter in order to support a procedural API

See also: itk::simple::NaryMaximumImageFilter for the object oriented interface

◆ NaryMaximum() [3/6]

Image itk::simple::NaryMaximum	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3
	)

Computes the pixel-wise maximum of several images.

This function directly calls the execute method of NaryMaximumImageFilter in order to support a procedural API

See also: itk::simple::NaryMaximumImageFilter for the object oriented interface

◆ NaryMaximum() [4/6]

Image itk::simple::NaryMaximum	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4
	)

Computes the pixel-wise maximum of several images.

This function directly calls the execute method of NaryMaximumImageFilter in order to support a procedural API

See also: itk::simple::NaryMaximumImageFilter for the object oriented interface

◆ NaryMaximum() [5/6]

Image itk::simple::NaryMaximum	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5
	)

Computes the pixel-wise maximum of several images.

This function directly calls the execute method of NaryMaximumImageFilter in order to support a procedural API

See also: itk::simple::NaryMaximumImageFilter for the object oriented interface

◆ NaryMaximum() [6/6]

Image itk::simple::NaryMaximum ( const std::vector< Image > & images )

Computes the pixel-wise maximum of several images.

This function directly calls the execute method of NaryMaximumImageFilter in order to support a procedural API

See also: itk::simple::NaryMaximumImageFilter for the object oriented interface

◆ NeighborhoodConnected()

Image itk::simple::NeighborhoodConnected	(	const Image &	image1,
		std::vector< std::vector< unsigned int > >	seedList = `std::vector< std::vector< unsigned int > >()`,
		double	lower = `0`,
		double	upper = `1`,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`,
		double	replaceValue = `1`
	)

Label pixels that are connected to a seed and lie within a neighborhood.

\ This function directly calls the execute method of NeighborhoodConnectedImageFilter in order to support a procedural API

See also: itk::simple::NeighborhoodConnectedImageFilter for the object oriented interface

◆ Noise()

Image itk::simple::Noise	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`
	)

Calculate the local noise in an image.

\ This function directly calls the execute method of NoiseImageFilter in order to support a procedural API

See also: itk::simple::NoiseImageFilter for the object oriented interface

◆ Normalize()

Image itk::simple::Normalize ( const Image & image1 )

Normalize an image by setting its mean to zero and variance to one.

\ This function directly calls the execute method of NormalizeImageFilter in order to support a procedural API

See also: itk::simple::NormalizeImageFilter for the object oriented interface

Examples: ImageRegistrationMethod2/ImageRegistrationMethod2.cxx.

Referenced by itk::simple::FFTConvolutionImageFilter::SetNormalize(), itk::simple::ConvolutionImageFilter::SetNormalize(), itk::simple::InverseDeconvolutionImageFilter::SetNormalize(), itk::simple::TikhonovDeconvolutionImageFilter::SetNormalize(), itk::simple::WienerDeconvolutionImageFilter::SetNormalize(), itk::simple::RichardsonLucyDeconvolutionImageFilter::SetNormalize(), itk::simple::ProjectedLandweberDeconvolutionImageFilter::SetNormalize(), and itk::simple::LandweberDeconvolutionImageFilter::SetNormalize().

◆ NormalizedCorrelation()

Image itk::simple::NormalizedCorrelation	(	const Image &	image,
		const Image &	maskImage,
		const Image &	templateImage
	)

Computes the normalized correlation of an image and a template.

\ This function directly calls the execute method of NormalizedCorrelationImageFilter in order to support a procedural API

See also: itk::simple::NormalizedCorrelationImageFilter for the object oriented interface

◆ NormalizeToConstant()

Image itk::simple::NormalizeToConstant	(	const Image &	image1,
		double	constant = `1.0`
	)

Scales image pixel intensities to make the sum of all pixels equal a user-defined constant.

\ This function directly calls the execute method of NormalizeToConstantImageFilter in order to support a procedural API

See also: itk::simple::NormalizeToConstantImageFilter for the object oriented interface

◆ Not() [1/2]

Image itk::simple::Not ( const Image & image1 )

Implements the NOT logical operator pixel-wise on an image.

\ This function directly calls the execute method of NotImageFilter in order to support a procedural API

See also: itk::simple::NotImageFilter for the object oriented interface

◆ Not() [2/2]

Image itk::simple::Not ( Image && image1 )

Implements the NOT logical operator pixel-wise on an image.

\ This function directly calls the execute method of NotImageFilter in order to support a procedural API

See also: itk::simple::NotImageFilter for the object oriented interface

◆ NotEqual() [1/5]

Image itk::simple::NotEqual	(	const Image &	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of NotEqualImageFilter in order to support a procedural API

See also: itk::simple::NotEqualImageFilter for the object oriented interface

◆ NotEqual() [2/5]

Image itk::simple::NotEqual	(	const Image &	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ NotEqual() [3/5]

Image itk::simple::NotEqual	(	double	constant,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ NotEqual() [4/5]

Image itk::simple::NotEqual	(	Image &&	image1,
		const Image &	image2,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

Implements pixel-wise generic operation of two images, or of an image and a constant.

\ This function directly calls the execute method of NotEqualImageFilter in order to support a procedural API

See also: itk::simple::NotEqualImageFilter for the object oriented interface

◆ NotEqual() [5/5]

Image itk::simple::NotEqual	(	Image &&	image1,
		double	constant,
		uint8_t	backgroundValue = `0u`,
		uint8_t	foregroundValue = `1u`
	)

◆ ObjectnessMeasure()

Image itk::simple::ObjectnessMeasure	(	const Image &	image1,
		double	alpha = `0.5`,
		double	beta = `0.5`,
		double	gamma = `5.0`,
		bool	scaleObjectnessMeasure = `true`,
		unsigned int	objectDimension = `1u`,
		bool	brightObject = `true`
	)

Enhance M-dimensional objects in N-dimensional images.

\ This function directly calls the execute method of ObjectnessMeasureImageFilter in order to support a procedural API

See also: itk::simple::ObjectnessMeasureImageFilter for the object oriented interface

◆ OpeningByReconstruction()

Image itk::simple::OpeningByReconstruction	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		bool	fullyConnected = `false`,
		bool	preserveIntensities = `false`
	)

Opening by reconstruction of an image.

\ This function directly calls the execute method of OpeningByReconstructionImageFilter in order to support a procedural API

See also: itk::simple::OpeningByReconstructionImageFilter for the object oriented interface

◆ operator%() [1/5]

Image itk::simple::operator%	(	const Image &	img,
		uint32_t	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 66 of file sitkImageOperators.h.

References Modulus().

◆ operator%() [2/5]

Image itk::simple::operator%	(	const Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 64 of file sitkImageOperators.h.

References Modulus().

◆ operator%() [3/5]

Image itk::simple::operator%	(	Image &&	img,
		uint32_t	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 67 of file sitkImageOperators.h.

References Modulus().

◆ operator%() [4/5]

Image itk::simple::operator%	(	Image &&	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 65 of file sitkImageOperators.h.

References Modulus().

◆ operator%() [5/5]

Image itk::simple::operator%	(	uint32_t	s,
		const Image &	img
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 68 of file sitkImageOperators.h.

References Modulus().

◆ operator%=() [1/2]

Image& itk::simple::operator%=	(	Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 104 of file sitkImageOperators.h.

References Modulus().

◆ operator%=() [2/2]

Image& itk::simple::operator%=	(	Image &	img1,
		uint32_t	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 105 of file sitkImageOperators.h.

References Modulus().

◆ operator&() [1/5]

Image itk::simple::operator&	(	const Image &	img,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 79 of file sitkImageOperators.h.

References And().

◆ operator&() [2/5]

Image itk::simple::operator&	(	const Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 77 of file sitkImageOperators.h.

References And().

◆ operator&() [3/5]

Image itk::simple::operator&	(	Image &&	img,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 80 of file sitkImageOperators.h.

References And().

◆ operator&() [4/5]

Image itk::simple::operator&	(	Image &&	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 78 of file sitkImageOperators.h.

References And().

◆ operator&() [5/5]

Image itk::simple::operator&	(	int	s,
		const Image &	img
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 81 of file sitkImageOperators.h.

References And().

◆ operator&=() [1/2]

Image& itk::simple::operator&=	(	Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 106 of file sitkImageOperators.h.

References And().

◆ operator&=() [2/2]

Image& itk::simple::operator&=	(	Image &	img1,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 107 of file sitkImageOperators.h.

References And().

◆ operator*() [1/5]

Image itk::simple::operator*	(	const Image &	img,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 56 of file sitkImageOperators.h.

References Multiply().

◆ operator*() [2/5]

Image itk::simple::operator*	(	const Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 54 of file sitkImageOperators.h.

References Multiply().

◆ operator*() [3/5]

Image itk::simple::operator*	(	double	s,
		const Image &	img
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 58 of file sitkImageOperators.h.

References Multiply().

◆ operator*() [4/5]

Image itk::simple::operator*	(	Image &&	img,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 57 of file sitkImageOperators.h.

References Multiply().

◆ operator*() [5/5]

Image itk::simple::operator*	(	Image &&	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 55 of file sitkImageOperators.h.

References Multiply().

◆ operator*=() [1/2]

Image& itk::simple::operator*=	(	Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 100 of file sitkImageOperators.h.

References Multiply().

◆ operator*=() [2/2]

Image& itk::simple::operator*=	(	Image &	img1,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 101 of file sitkImageOperators.h.

References Multiply().

◆ operator+() [1/5]

Image itk::simple::operator+	(	const Image &	img,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 46 of file sitkImageOperators.h.

References Add().

◆ operator+() [2/5]

Image itk::simple::operator+	(	const Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 44 of file sitkImageOperators.h.

References Add().

◆ operator+() [3/5]

Image itk::simple::operator+	(	double	s,
		const Image &	img
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 48 of file sitkImageOperators.h.

References Add().

◆ operator+() [4/5]

Image itk::simple::operator+	(	Image &&	img,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 47 of file sitkImageOperators.h.

References Add().

◆ operator+() [5/5]

Image itk::simple::operator+	(	Image &&	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 45 of file sitkImageOperators.h.

References Add().

◆ operator+=() [1/2]

Image& itk::simple::operator+=	(	Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 96 of file sitkImageOperators.h.

References Add().

◆ operator+=() [2/2]

Image& itk::simple::operator+=	(	Image &	img1,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 97 of file sitkImageOperators.h.

References Add().

◆ operator-() [1/7]

Image itk::simple::operator- ( const Image & img )

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 70 of file sitkImageOperators.h.

References UnaryMinus().

◆ operator-() [2/7]

Image itk::simple::operator-	(	const Image &	img,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 51 of file sitkImageOperators.h.

References Subtract().

◆ operator-() [3/7]

Image itk::simple::operator-	(	const Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 49 of file sitkImageOperators.h.

References Subtract().

◆ operator-() [4/7]

Image itk::simple::operator-	(	double	s,
		const Image &	img
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 53 of file sitkImageOperators.h.

References Subtract().

◆ operator-() [5/7]

Image itk::simple::operator- ( Image && img )

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 71 of file sitkImageOperators.h.

References UnaryMinus().

◆ operator-() [6/7]

Image itk::simple::operator-	(	Image &&	img,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 52 of file sitkImageOperators.h.

References Subtract().

◆ operator-() [7/7]

Image itk::simple::operator-	(	Image &&	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 50 of file sitkImageOperators.h.

References Subtract().

◆ operator-=() [1/2]

Image& itk::simple::operator-=	(	Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 98 of file sitkImageOperators.h.

References Subtract().

◆ operator-=() [2/2]

Image& itk::simple::operator-=	(	Image &	img1,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 99 of file sitkImageOperators.h.

References Subtract().

◆ operator/() [1/5]

Image itk::simple::operator/	(	const Image &	img,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 61 of file sitkImageOperators.h.

References Divide().

◆ operator/() [2/5]

Image itk::simple::operator/	(	const Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 59 of file sitkImageOperators.h.

References Divide().

◆ operator/() [3/5]

Image itk::simple::operator/	(	double	s,
		const Image &	img
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 63 of file sitkImageOperators.h.

References Divide().

◆ operator/() [4/5]

Image itk::simple::operator/	(	Image &&	img,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 62 of file sitkImageOperators.h.

References Divide().

◆ operator/() [5/5]

Image itk::simple::operator/	(	Image &&	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 60 of file sitkImageOperators.h.

References Divide().

◆ operator/=() [1/2]

Image& itk::simple::operator/=	(	Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 102 of file sitkImageOperators.h.

References Divide().

◆ operator/=() [2/2]

Image& itk::simple::operator/=	(	Image &	img1,
		double	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 103 of file sitkImageOperators.h.

References Divide().

◆ operator<<() [1/5]

SITKCommon_EXPORT std::ostream& itk::simple::operator<<	(	std::ostream &	os,
		const EventEnum	k
	)

◆ operator<<() [2/5]

SITKCommon_EXPORT std::ostream& itk::simple::operator<<	(	std::ostream &	os,
		const InterpolatorEnum	i
	)

Convert Interpolator enum to a string for printing etc..

◆ operator<<() [3/5]

SITKCommon_EXPORT std::ostream& itk::simple::operator<<	(	std::ostream &	os,
		const KernelEnum	k
	)

◆ operator<<() [4/5]

SITKCommon_EXPORT std::ostream& itk::simple::operator<<	(	std::ostream &	os,
		const PixelIDValueEnum	id
	)

◆ operator<<() [5/5]

template<typename T >

SITKCommon_HIDDEN std::ostream& itk::simple::operator<<	(	std::ostream &	os,
		const std::vector< T > &	v
	)

Output the element of an std::vector to the output stream.

The elements of the std::vector are required to have operator<<.

The format of the output should be "[ T, T, T ]".

Definition at line 52 of file sitkTemplateFunctions.h.

◆ operator^() [1/5]

Image itk::simple::operator^	(	const Image &	img,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 91 of file sitkImageOperators.h.

References Xor().

◆ operator^() [2/5]

Image itk::simple::operator^	(	const Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 89 of file sitkImageOperators.h.

References Xor().

◆ operator^() [3/5]

Image itk::simple::operator^	(	Image &&	img,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 92 of file sitkImageOperators.h.

References Xor().

◆ operator^() [4/5]

Image itk::simple::operator^	(	Image &&	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 90 of file sitkImageOperators.h.

References Xor().

◆ operator^() [5/5]

Image itk::simple::operator^	(	int	s,
		const Image &	img
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 93 of file sitkImageOperators.h.

References Xor().

◆ operator^=() [1/2]

Image& itk::simple::operator^=	(	Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 110 of file sitkImageOperators.h.

References Xor().

◆ operator^=() [2/2]

Image& itk::simple::operator^=	(	Image &	img1,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 111 of file sitkImageOperators.h.

References Xor().

◆ operator|() [1/5]

Image itk::simple::operator\|	(	const Image &	img,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 85 of file sitkImageOperators.h.

References Or().

◆ operator|() [2/5]

Image itk::simple::operator\|	(	const Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 83 of file sitkImageOperators.h.

References Or().

◆ operator|() [3/5]

Image itk::simple::operator\|	(	Image &&	img,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 86 of file sitkImageOperators.h.

References Or().

◆ operator|() [4/5]

Image itk::simple::operator\|	(	Image &&	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 84 of file sitkImageOperators.h.

References Or().

◆ operator|() [5/5]

Image itk::simple::operator\|	(	int	s,
		const Image &	img
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 87 of file sitkImageOperators.h.

References Or().

◆ operator|=() [1/2]

Image& itk::simple::operator\|=	(	Image &	img1,
		const Image &	img2
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 108 of file sitkImageOperators.h.

References Or().

◆ operator|=() [2/2]

Image& itk::simple::operator\|=	(	Image &	img1,
		int	s
	)

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 109 of file sitkImageOperators.h.

References Or().

◆ operator~() [1/2]

Image itk::simple::operator~ ( const Image & img )

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 74 of file sitkImageOperators.h.

References BitwiseNot().

◆ operator~() [2/2]

Image itk::simple::operator~ ( Image && img )

inline

Performs the operator on a per pixel basis.

All overloaded simpleITK operators are performed on a per-pixel basis, and implemented with the corresponding image filters. These operators gernerally don't work with label images, and the logical operators don't work with images of real components or vector images.

Definition at line 75 of file sitkImageOperators.h.

References BitwiseNot().

◆ Or() [1/5]

Image itk::simple::Or	(	const Image &	image1,
		const Image &	image2
	)

Implements the OR bitwise operator pixel-wise between two images.

\ This function directly calls the execute method of OrImageFilter in order to support a procedural API

See also: itk::simple::OrImageFilter for the object oriented interface

◆ Or() [2/5]

Image itk::simple::Or	(	const Image &	image1,
		int	constant
	)

◆ Or() [3/5]

Image itk::simple::Or	(	Image &&	image1,
		const Image &	image2
	)

Implements the OR bitwise operator pixel-wise between two images.

\ This function directly calls the execute method of OrImageFilter in order to support a procedural API

See also: itk::simple::OrImageFilter for the object oriented interface

Referenced by operator|(), and operator|=().

◆ Or() [4/5]

Image itk::simple::Or	(	Image &&	image1,
		int	constant
	)

◆ Or() [5/5]

Image itk::simple::Or	(	int	constant,
		const Image &	image2
	)

◆ OtsuMultipleThresholds()

Image itk::simple::OtsuMultipleThresholds	(	const Image &	image1,
		uint8_t	numberOfThresholds = `1u`,
		uint8_t	labelOffset = `0u`,
		uint32_t	numberOfHistogramBins = `128u`,
		bool	valleyEmphasis = `false`,
		bool	returnBinMidpoint = `false`
	)

Threshold an image using multiple Otsu Thresholds.

\ This function directly calls the execute method of OtsuMultipleThresholdsImageFilter in order to support a procedural API

See also: itk::simple::OtsuMultipleThresholdsImageFilter for the object oriented interface

◆ OtsuThreshold() [1/2]

Image itk::simple::OtsuThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `128u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`,
		bool	returnBinMidpoint = `false`
	)

Threshold an image using the Otsu Threshold.

\ This function directly calls the execute method of OtsuThresholdImageFilter in order to support a procedural API

See also: itk::simple::OtsuThresholdImageFilter for the object oriented interface

◆ OtsuThreshold() [2/2]

Image itk::simple::OtsuThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `128u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`,
		bool	returnBinMidpoint = `false`
	)

Threshold an image using the Otsu Threshold.

\ This function directly calls the execute method of OtsuThresholdImageFilter in order to support a procedural API

See also: itk::simple::OtsuThresholdImageFilter for the object oriented interface

◆ Paste() [1/2]

Image itk::simple::Paste	(	const Image &	destinationImage,
		const Image &	sourceImage,
		std::vector< unsigned int >	sourceSize = `std::vector< unsigned int >(SITK_MAX_DIMENSION, 1)`,
		std::vector< int >	sourceIndex = `std::vector< int >(SITK_MAX_DIMENSION, 0)`,
		std::vector< int >	destinationIndex = `std::vector< int >(SITK_MAX_DIMENSION, 0)`,
		std::vector< bool >	DestinationSkipAxes = `std::vector< bool >()`
	)

Paste an image into another image.

\ This function directly calls the execute method of PasteImageFilter in order to support a procedural API

See also: itk::simple::PasteImageFilter for the object oriented interface

◆ Paste() [2/2]

Image itk::simple::Paste	(	Image &&	destinationImage,
		const Image &	sourceImage,
		std::vector< unsigned int >	sourceSize = `std::vector< unsigned int >(SITK_MAX_DIMENSION, 1)`,
		std::vector< int >	sourceIndex = `std::vector< int >(SITK_MAX_DIMENSION, 0)`,
		std::vector< int >	destinationIndex = `std::vector< int >(SITK_MAX_DIMENSION, 0)`,
		std::vector< bool >	DestinationSkipAxes = `std::vector< bool >()`
	)

Paste an image into another image.

\ This function directly calls the execute method of PasteImageFilter in order to support a procedural API

See also: itk::simple::PasteImageFilter for the object oriented interface

Examples: HelloWorld/HelloWorld.cxx.

◆ PatchBasedDenoising() [1/2]

Image itk::simple::PatchBasedDenoising	(	const Image &	image1,
		double	kernelBandwidthSigma = `400.0`,
		uint32_t	patchRadius = `4u`,
		uint32_t	numberOfIterations = `1u`,
		uint32_t	numberOfSamplePatches = `200u`,
		double	sampleVariance = `400.0`
	)

◆ PatchBasedDenoising() [2/2]

Image itk::simple::PatchBasedDenoising	(	const Image &	image1,
		itk::simple::PatchBasedDenoisingImageFilter::NoiseModelType	noiseModel,
		double	kernelBandwidthSigma = `400.0`,
		uint32_t	patchRadius = `4u`,
		uint32_t	numberOfIterations = `1u`,
		uint32_t	numberOfSamplePatches = `200u`,
		double	sampleVariance = `400.0`,
		double	noiseSigma = `0.0`,
		double	noiseModelFidelityWeight = `0.0`
	)

itk::simple::PatchBasedDenoisingImageFilter Procedural Interface

This function directly calls the execute method of PatchBasedDenoisingImageFilter in order to support a procedural API

See also: itk::simple::PatchBasedDenoisingImageFilter for the object oriented interface

◆ PermuteAxes()

Image itk::simple::PermuteAxes	(	const Image &	image1,
		std::vector< unsigned int >	order = `std::vector< unsigned int >(&itk::simple::PermuteAxesImageFilter::DefaultOrder[0], &itk::simple::PermuteAxesImageFilter::DefaultOrder[3])`
	)

Permutes the image axes according to a user specified order.

\ This function directly calls the execute method of PermuteAxesImageFilter in order to support a procedural API

See also: itk::simple::PermuteAxesImageFilter for the object oriented interface

◆ PhysicalPointSource()

Image itk::simple::PhysicalPointSource	(	PixelIDValueEnum	outputPixelType = `itk::simple::sitkVectorFloat32`,
		std::vector< unsigned int >	size = `std::vector< unsigned int >(3, 64)`,
		std::vector< double >	origin = `std::vector< double >(3, 0.0)`,
		std::vector< double >	spacing = `std::vector< double >(3, 1.0)`,
		std::vector< double >	direction = `std::vector< double >()`
	)

Generate an image of the physical locations of each pixel.

This function directly calls the execute method of PhysicalPointImageSource in order to support a procedural API

See also: itk::simple::PhysicalPointImageSource for the object oriented interface

◆ Pow() [1/5]

Image itk::simple::Pow	(	const Image &	image1,
		const Image &	image2
	)

Computes the powers of 2 images.

\ This function directly calls the execute method of PowImageFilter in order to support a procedural API

See also: itk::simple::PowImageFilter for the object oriented interface

◆ Pow() [2/5]

Image itk::simple::Pow	(	const Image &	image1,
		double	constant
	)

◆ Pow() [3/5]

Image itk::simple::Pow	(	double	constant,
		const Image &	image2
	)

◆ Pow() [4/5]

Image itk::simple::Pow	(	Image &&	image1,
		const Image &	image2
	)

Computes the powers of 2 images.

\ This function directly calls the execute method of PowImageFilter in order to support a procedural API

See also: itk::simple::PowImageFilter for the object oriented interface

◆ Pow() [5/5]

Image itk::simple::Pow	(	Image &&	image1,
		double	constant
	)

◆ ProjectedLandweberDeconvolution()

Image itk::simple::ProjectedLandweberDeconvolution	(	const Image &	image1,
		const Image &	image2,
		double	alpha = `0.1`,
		int	numberOfIterations = `1`,
		bool	normalize = `false`,
		ProjectedLandweberDeconvolutionImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::ProjectedLandweberDeconvolutionImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		ProjectedLandweberDeconvolutionImageFilter::OutputRegionModeType	outputRegionMode = `itk::simple::ProjectedLandweberDeconvolutionImageFilter::SAME`
	)

Deconvolve an image using the projected Landweber deconvolution algorithm.

\ This function directly calls the execute method of ProjectedLandweberDeconvolutionImageFilter in order to support a procedural API

See also: itk::simple::ProjectedLandweberDeconvolutionImageFilter for the object oriented interface

◆ Rank()

Image itk::simple::Rank	(	const Image &	image1,
		double	rank = `0.5`,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`
	)

Rank filter of a greyscale image.

\ This function directly calls the execute method of RankImageFilter in order to support a procedural API

See also: itk::simple::RankImageFilter for the object oriented interface

Referenced by itk::simple::FastApproximateRankImageFilter::SetRank(), and itk::simple::RankImageFilter::SetRank().

◆ ReadImage() [1/2]

SITKIO_EXPORT Image itk::simple::ReadImage	(	const std::string &	filename,
		PixelIDValueEnum	outputPixelType = `sitkUnknown`,
		const std::string &	imageIO = `""`
	)

ReadImage is a procedural interface to the ImageFileReader class which is convenient for most image reading tasks.

Parameters

filename	the filename of an Image e.g. "cthead.mha"
outputPixelType	see ImageReaderBase::SetOutputPixelType
imageIO	see ImageReaderBase::SetImageIO

See also: itk::simple::ImageFileReader for reading a single file.; itk::simple::ImageSeriesReader for reading a series and meta-data dictionaries.

Examples: DemonsRegistration1/DemonsRegistration1.cxx, DemonsRegistration2/DemonsRegistration2.cxx, FastMarchingSegmentation/FastMarchingSegmentation.cxx, ImageRegistrationMethod1/ImageRegistrationMethod1.cxx, ImageRegistrationMethod2/ImageRegistrationMethod2.cxx, ImageRegistrationMethodBSpline1/ImageRegistrationMethodBSpline1.cxx, ImageRegistrationMethodBSpline3/ImageRegistrationMethodBSpline3.cxx, ImageRegistrationMethodDisplacement1/ImageRegistrationMethodDisplacement1.cxx, SimpleGaussianFunctional.cxx, and SliceBySliceDecorator/SliceBySliceDecorator.cxx.

◆ ReadImage() [2/2]

SITKIO_EXPORT Image itk::simple::ReadImage	(	const std::vector< std::string > &	fileNames,
		PixelIDValueEnum	outputPixelType = `sitkUnknown`,
		const std::string &	imageIO = `""`
	)

ReadImage is a procedural interface to the ImageSeriesReader class which is convenient for most image reading tasks.

Parameters

fileNames	a vector of file names
outputPixelType	see ImageReaderBase::SetOutputPixelType
imageIO	see ImageReaderBase::SetImageIO

Note: When reading a series of images that have meta-data associated with them (e.g. a DICOM series) the resulting image will have an empty meta-data dictionary. If you need the meta-data dictionaries associated with each slice then you should use the ImageSeriesReader class.

See also: itk::simple::ImageFileReader for reading a single file.; itk::simple::ImageSeriesReader for reading a series and meta-data dictionaries.

◆ ReadTransform()

SITKCommon_EXPORT Transform itk::simple::ReadTransform ( const std::string & filename )

Examples: DemonsRegistration2/DemonsRegistration2.cxx.

◆ RealAndImaginaryToComplex()

Image itk::simple::RealAndImaginaryToComplex	(	const Image &	image1,
		const Image &	image2
	)

ComposeImageFilter combine several scalar images into a multicomponent image.

\ This function directly calls the execute method of RealAndImaginaryToComplexImageFilter in order to support a procedural API

See also: itk::simple::RealAndImaginaryToComplexImageFilter for the object oriented interface

◆ RealToHalfHermitianForwardFFT()

Image itk::simple::RealToHalfHermitianForwardFFT ( const Image & image1 )

Base class for specialized real-to-complex forward Fast Fourier Transform .

\ This function directly calls the execute method of RealToHalfHermitianForwardFFTImageFilter in order to support a procedural API

See also: itk::simple::RealToHalfHermitianForwardFFTImageFilter for the object oriented interface

◆ ReconstructionByDilation()

Image itk::simple::ReconstructionByDilation	(	const Image &	markerImage,
		const Image &	maskImage,
		bool	fullyConnected = `false`,
		bool	useInternalCopy = `true`
	)

grayscale reconstruction by dilation of an image

\ This function directly calls the execute method of ReconstructionByDilationImageFilter in order to support a procedural API

See also: itk::simple::ReconstructionByDilationImageFilter for the object oriented interface

◆ ReconstructionByErosion()

Image itk::simple::ReconstructionByErosion	(	const Image &	markerImage,
		const Image &	maskImage,
		bool	fullyConnected = `false`,
		bool	useInternalCopy = `true`
	)

grayscale reconstruction by erosion of an image

\ This function directly calls the execute method of ReconstructionByErosionImageFilter in order to support a procedural API

See also: itk::simple::ReconstructionByErosionImageFilter for the object oriented interface

◆ RecursiveGaussian() [1/2]

Image itk::simple::RecursiveGaussian	(	const Image &	image1,
		double	sigma = `1.0`,
		bool	normalizeAcrossScale = `false`,
		RecursiveGaussianImageFilter::OrderType	order = `itk::simple::RecursiveGaussianImageFilter::ZeroOrder`,
		unsigned int	direction = `0u`
	)

Base class for computing IIR convolution with an approximation of a Gaussian kernel.

\ This function directly calls the execute method of RecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::RecursiveGaussianImageFilter for the object oriented interface

◆ RecursiveGaussian() [2/2]

Image itk::simple::RecursiveGaussian	(	Image &&	image1,
		double	sigma = `1.0`,
		bool	normalizeAcrossScale = `false`,
		RecursiveGaussianImageFilter::OrderType	order = `itk::simple::RecursiveGaussianImageFilter::ZeroOrder`,
		unsigned int	direction = `0u`
	)

Base class for computing IIR convolution with an approximation of a Gaussian kernel.

\ This function directly calls the execute method of RecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::RecursiveGaussianImageFilter for the object oriented interface

◆ RegionalMaxima()

Image itk::simple::RegionalMaxima	(	const Image &	image1,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`,
		bool	fullyConnected = `false`,
		bool	flatIsMaxima = `true`
	)

Produce a binary image where foreground is the regional maxima of the input image.

\ This function directly calls the execute method of RegionalMaximaImageFilter in order to support a procedural API

See also: itk::simple::RegionalMaximaImageFilter for the object oriented interface

◆ RegionalMinima()

Image itk::simple::RegionalMinima	(	const Image &	image1,
		double	backgroundValue = `0.0`,
		double	foregroundValue = `1.0`,
		bool	fullyConnected = `false`,
		bool	flatIsMinima = `true`
	)

Produce a binary image where foreground is the regional minima of the input image.

\ This function directly calls the execute method of RegionalMinimaImageFilter in order to support a procedural API

See also: itk::simple::RegionalMinimaImageFilter for the object oriented interface

◆ RegionOfInterest()

Image itk::simple::RegionOfInterest	(	const Image &	image1,
		std::vector< unsigned int >	size = `std::vector< unsigned int >(3, 1)`,
		std::vector< int >	index = `std::vector< int >(3, 0)`
	)

Extract a region of interest from the input image.

\ This function directly calls the execute method of RegionOfInterestImageFilter in order to support a procedural API

See also: itk::simple::RegionOfInterestImageFilter for the object oriented interface

◆ RelabelComponent() [1/2]

Image itk::simple::RelabelComponent	(	const Image &	image1,
		uint64_t	minimumObjectSize = `0u`,
		bool	sortByObjectSize = `true`
	)

Relabel the components in an image such that consecutive labels are used.

\ This function directly calls the execute method of RelabelComponentImageFilter in order to support a procedural API

See also: itk::simple::RelabelComponentImageFilter for the object oriented interface

◆ RelabelComponent() [2/2]

Image itk::simple::RelabelComponent	(	Image &&	image1,
		uint64_t	minimumObjectSize = `0u`,
		bool	sortByObjectSize = `true`
	)

Relabel the components in an image such that consecutive labels are used.

\ This function directly calls the execute method of RelabelComponentImageFilter in order to support a procedural API

See also: itk::simple::RelabelComponentImageFilter for the object oriented interface

◆ RelabelLabelMap() [1/2]

Image itk::simple::RelabelLabelMap	(	const Image &	image1,
		bool	reverseOrdering = `true`
	)

This filter relabels the LabelObjects; the new labels are arranged consecutively with consideration for the background value.

\ This function directly calls the execute method of RelabelLabelMapFilter in order to support a procedural API

See also: itk::simple::RelabelLabelMapFilter for the object oriented interface

◆ RelabelLabelMap() [2/2]

Image itk::simple::RelabelLabelMap	(	Image &&	image1,
		bool	reverseOrdering = `true`
	)

This filter relabels the LabelObjects; the new labels are arranged consecutively with consideration for the background value.

\ This function directly calls the execute method of RelabelLabelMapFilter in order to support a procedural API

See also: itk::simple::RelabelLabelMapFilter for the object oriented interface

◆ RenyiEntropyThreshold() [1/2]

Image itk::simple::RenyiEntropyThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the RenyiEntropy Threshold.

\ This function directly calls the execute method of RenyiEntropyThresholdImageFilter in order to support a procedural API

See also: itk::simple::RenyiEntropyThresholdImageFilter for the object oriented interface

◆ RenyiEntropyThreshold() [2/2]

Image itk::simple::RenyiEntropyThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the RenyiEntropy Threshold.

\ This function directly calls the execute method of RenyiEntropyThresholdImageFilter in order to support a procedural API

See also: itk::simple::RenyiEntropyThresholdImageFilter for the object oriented interface

◆ Resample() [1/3]

Image itk::simple::Resample	(	const Image &	image1,
		const Image &	referenceImage,
		Transform	transform = `itk::simple::Transform()`,
		InterpolatorEnum	interpolator = `itk::simple::sitkLinear`,
		double	defaultPixelValue = `0.0`,
		PixelIDValueEnum	outputPixelType = `sitkUnknown`,
		bool	useNearestNeighborExtrapolator = `false`
	)

itk::simple::ResampleImageFilter Procedural Interface

These functions call the execute method of ResampleImageFilter in order to support a procedual API.

The difference between the three functions is in the way the output image's domain parameters are specified (origin, spacing, direction). The first function uses the parameters from the input image, the second uses the parameters of a reference image, and the third uses explicitly specified parameters.

See also: itk::simple::ResampleImageFilter for the object oriented interface

◆ Resample() [2/3]

Image itk::simple::Resample	(	const Image &	image1,
		const std::vector< uint32_t > &	size,
		Transform	transform = `itk::simple::Transform()`,
		InterpolatorEnum	interpolator = `itk::simple::sitkLinear`,
		const std::vector< double > &	outputOrigin = `std::vector< double >(3, 0.0)`,
		const std::vector< double > &	outputSpacing = `std::vector< double >(3, 1.0)`,
		const std::vector< double > &	outputDirection = `std::vector< double >()`,
		double	defaultPixelValue = `0.0`,
		PixelIDValueEnum	outputPixelType = `sitkUnknown`,
		bool	useNearestNeighborExtrapolator = `false`
	)

itk::simple::ResampleImageFilter Procedural Interface

These functions call the execute method of ResampleImageFilter in order to support a procedual API.

The difference between the three functions is in the way the output image's domain parameters are specified (origin, spacing, direction). The first function uses the parameters from the input image, the second uses the parameters of a reference image, and the third uses explicitly specified parameters.

See also: itk::simple::ResampleImageFilter for the object oriented interface

◆ Resample() [3/3]

Image itk::simple::Resample	(	const Image &	image1,
		Transform	transform = `itk::simple::Transform()`,
		InterpolatorEnum	interpolator = `itk::simple::sitkLinear`,
		double	defaultPixelValue = `0.0`,
		PixelIDValueEnum	outputPixelType = `sitkUnknown`,
		bool	useNearestNeighborExtrapolator = `false`
	)

itk::simple::ResampleImageFilter Procedural Interface

These functions call the execute method of ResampleImageFilter in order to support a procedual API.

The difference between the three functions is in the way the output image's domain parameters are specified (origin, spacing, direction). The first function uses the parameters from the input image, the second uses the parameters of a reference image, and the third uses explicitly specified parameters.

See also: itk::simple::ResampleImageFilter for the object oriented interface

◆ RescaleIntensity() [1/2]

Image itk::simple::RescaleIntensity	(	const Image &	image1,
		double	outputMinimum = `0`,
		double	outputMaximum = `255`
	)

Applies a linear transformation to the intensity levels of the input Image .

\ This function directly calls the execute method of RescaleIntensityImageFilter in order to support a procedural API

See also: itk::simple::RescaleIntensityImageFilter for the object oriented interface

◆ RescaleIntensity() [2/2]

Image itk::simple::RescaleIntensity	(	Image &&	image1,
		double	outputMinimum = `0`,
		double	outputMaximum = `255`
	)

Applies a linear transformation to the intensity levels of the input Image .

\ This function directly calls the execute method of RescaleIntensityImageFilter in order to support a procedural API

See also: itk::simple::RescaleIntensityImageFilter for the object oriented interface

◆ RichardsonLucyDeconvolution()

Image itk::simple::RichardsonLucyDeconvolution	(	const Image &	image1,
		const Image &	image2,
		int	numberOfIterations = `1`,
		bool	normalize = `false`,
		RichardsonLucyDeconvolutionImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::RichardsonLucyDeconvolutionImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		RichardsonLucyDeconvolutionImageFilter::OutputRegionModeType	outputRegionMode = `itk::simple::RichardsonLucyDeconvolutionImageFilter::SAME`
	)

Deconvolve an image using the Richardson-Lucy deconvolution algorithm.

\ This function directly calls the execute method of RichardsonLucyDeconvolutionImageFilter in order to support a procedural API

See also: itk::simple::RichardsonLucyDeconvolutionImageFilter for the object oriented interface

◆ Round() [1/2]

Image itk::simple::Round ( const Image & image1 )

Rounds the value of each pixel.

\ This function directly calls the execute method of RoundImageFilter in order to support a procedural API

See also: itk::simple::RoundImageFilter for the object oriented interface

◆ Round() [2/2]

Image itk::simple::Round ( Image && image1 )

Rounds the value of each pixel.

\ This function directly calls the execute method of RoundImageFilter in order to support a procedural API

See also: itk::simple::RoundImageFilter for the object oriented interface

◆ SaltAndPepperNoise() [1/2]

Image itk::simple::SaltAndPepperNoise	(	const Image &	image1,
		double	probability = `0.01`,
		uint32_t	seed = `(uint32_t) itk::simple::sitkWallClock`
	)

Alter an image with fixed value impulse noise, often called salt and pepper noise.

\ This function directly calls the execute method of SaltAndPepperNoiseImageFilter in order to support a procedural API

See also: itk::simple::SaltAndPepperNoiseImageFilter for the object oriented interface

◆ SaltAndPepperNoise() [2/2]

Image itk::simple::SaltAndPepperNoise	(	Image &&	image1,
		double	probability = `0.01`,
		uint32_t	seed = `(uint32_t) itk::simple::sitkWallClock`
	)

Alter an image with fixed value impulse noise, often called salt and pepper noise.

\ This function directly calls the execute method of SaltAndPepperNoiseImageFilter in order to support a procedural API

See also: itk::simple::SaltAndPepperNoiseImageFilter for the object oriented interface

◆ ScalarChanAndVeseDenseLevelSet()

Image itk::simple::ScalarChanAndVeseDenseLevelSet	(	const Image &	initialImage,
		const Image &	featureImage,
		double	maximumRMSError = `0.02`,
		uint32_t	numberOfIterations = `1000u`,
		double	lambda1 = `1.0`,
		double	lambda2 = `1.0`,
		double	epsilon = `1.0`,
		double	curvatureWeight = `1.0`,
		double	areaWeight = `0.0`,
		double	reinitializationSmoothingWeight = `0.0`,
		double	volume = `0.0`,
		double	volumeMatchingWeight = `0.0`,
		ScalarChanAndVeseDenseLevelSetImageFilter::HeavisideStepFunctionType	heavisideStepFunction = `itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::AtanRegularizedHeaviside`,
		bool	useImageSpacing = `true`
	)

Dense implementation of the Chan and Vese multiphase level set image filter.

\ This function directly calls the execute method of ScalarChanAndVeseDenseLevelSetImageFilter in order to support a procedural API

See also: itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter for the object oriented interface

◆ ScalarConnectedComponent() [1/2]

Image itk::simple::ScalarConnectedComponent	(	const Image &	image,
		const Image &	maskImage,
		double	distanceThreshold = `0.0`,
		bool	fullyConnected = `false`
	)

A connected components filter that labels the objects in an arbitrary image. Two pixels are similar if they are within threshold of each other. Uses ConnectedComponentFunctorImageFilter .

\ This function directly calls the execute method of ScalarConnectedComponentImageFilter in order to support a procedural API

See also: itk::simple::ScalarConnectedComponentImageFilter for the object oriented interface

◆ ScalarConnectedComponent() [2/2]

Image itk::simple::ScalarConnectedComponent	(	const Image &	image,
		double	distanceThreshold = `0.0`,
		bool	fullyConnected = `false`
	)

A connected components filter that labels the objects in an arbitrary image. Two pixels are similar if they are within threshold of each other. Uses ConnectedComponentFunctorImageFilter .

\ This function directly calls the execute method of ScalarConnectedComponentImageFilter in order to support a procedural API

See also: itk::simple::ScalarConnectedComponentImageFilter for the object oriented interface

◆ ScalarImageKmeans()

Image itk::simple::ScalarImageKmeans	(	const Image &	image1,
		std::vector< double >	classWithInitialMean = `std::vector< double >()`,
		bool	useNonContiguousLabels = `false`
	)

Classifies the intensity values of a scalar image using the K-Means algorithm.

\ This function directly calls the execute method of ScalarImageKmeansImageFilter in order to support a procedural API

See also: itk::simple::ScalarImageKmeansImageFilter for the object oriented interface

◆ ScalarToRGBColormap()

Image itk::simple::ScalarToRGBColormap	(	const Image &	image1,
		ScalarToRGBColormapImageFilter::ColormapType	colormap = `itk::simple::ScalarToRGBColormapImageFilter::Grey`,
		bool	useInputImageExtremaForScaling = `true`
	)

Implements pixel-wise intensity->rgb mapping operation on one image.

\ This function directly calls the execute method of ScalarToRGBColormapImageFilter in order to support a procedural API

See also: itk::simple::ScalarToRGBColormapImageFilter for the object oriented interface

◆ ShanbhagThreshold() [1/2]

Image itk::simple::ShanbhagThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Shanbhag Threshold.

\ This function directly calls the execute method of ShanbhagThresholdImageFilter in order to support a procedural API

See also: itk::simple::ShanbhagThresholdImageFilter for the object oriented interface

◆ ShanbhagThreshold() [2/2]

Image itk::simple::ShanbhagThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Shanbhag Threshold.

\ This function directly calls the execute method of ShanbhagThresholdImageFilter in order to support a procedural API

See also: itk::simple::ShanbhagThresholdImageFilter for the object oriented interface

◆ ShapeDetectionLevelSet() [1/2]

Image itk::simple::ShapeDetectionLevelSet	(	const Image &	initialImage,
		const Image &	featureImage,
		double	maximumRMSError = `0.02`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`
	)

Segments structures in images based on a user supplied edge potential map.

\ This function directly calls the execute method of ShapeDetectionLevelSetImageFilter in order to support a procedural API

See also: itk::simple::ShapeDetectionLevelSetImageFilter for the object oriented interface

◆ ShapeDetectionLevelSet() [2/2]

Image itk::simple::ShapeDetectionLevelSet	(	Image &&	initialImage,
		const Image &	featureImage,
		double	maximumRMSError = `0.02`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`
	)

Segments structures in images based on a user supplied edge potential map.

\ This function directly calls the execute method of ShapeDetectionLevelSetImageFilter in order to support a procedural API

See also: itk::simple::ShapeDetectionLevelSetImageFilter for the object oriented interface

◆ ShiftScale()

Image itk::simple::ShiftScale	(	const Image &	image1,
		double	shift = `0`,
		double	scale = `1.0`
	)

Shift and scale the pixels in an image.

\ This function directly calls the execute method of ShiftScaleImageFilter in order to support a procedural API

See also: itk::simple::ShiftScaleImageFilter for the object oriented interface

◆ ShotNoise() [1/2]

Image itk::simple::ShotNoise	(	const Image &	image1,
		double	scale = `1.0`,
		uint32_t	seed = `(uint32_t) itk::simple::sitkWallClock`
	)

Alter an image with shot noise.

\ This function directly calls the execute method of ShotNoiseImageFilter in order to support a procedural API

See also: itk::simple::ShotNoiseImageFilter for the object oriented interface

◆ ShotNoise() [2/2]

Image itk::simple::ShotNoise	(	Image &&	image1,
		double	scale = `1.0`,
		uint32_t	seed = `(uint32_t) itk::simple::sitkWallClock`
	)

Alter an image with shot noise.

\ This function directly calls the execute method of ShotNoiseImageFilter in order to support a procedural API

See also: itk::simple::ShotNoiseImageFilter for the object oriented interface

◆ Show()

void SITKIO_EXPORT itk::simple::Show	(	const Image &	image,
		const std::string &	title = `""`,
		const bool	debugOn = `ProcessObject::GetGlobalDefaultDebug()`
	)

Display an image in an external viewer (Fiji by default)

This function directly calls the execute method of ImageViewer in order to support a procedural API

Examples: BufferImportExport.cxx, and HelloWorld/HelloWorld.cxx.

◆ Shrink()

Image itk::simple::Shrink	(	const Image &	image1,
		std::vector< unsigned int >	shrinkFactors = `std::vector< unsigned int >(3, 1)`
	)

Reduce the size of an image by an integer factor in each dimension.

\ This function directly calls the execute method of ShrinkImageFilter in order to support a procedural API

See also: itk::simple::ShrinkImageFilter for the object oriented interface

◆ Sigmoid() [1/2]

Image itk::simple::Sigmoid	(	const Image &	image1,
		double	alpha = `1`,
		double	beta = `0`,
		double	outputMaximum = `255`,
		double	outputMinimum = `0`
	)

Computes the sigmoid function pixel-wise.

\ This function directly calls the execute method of SigmoidImageFilter in order to support a procedural API

See also: itk::simple::SigmoidImageFilter for the object oriented interface

◆ Sigmoid() [2/2]

Image itk::simple::Sigmoid	(	Image &&	image1,
		double	alpha = `1`,
		double	beta = `0`,
		double	outputMaximum = `255`,
		double	outputMinimum = `0`
	)

Computes the sigmoid function pixel-wise.

\ This function directly calls the execute method of SigmoidImageFilter in order to support a procedural API

See also: itk::simple::SigmoidImageFilter for the object oriented interface

◆ SignedDanielssonDistanceMap()

Image itk::simple::SignedDanielssonDistanceMap	(	const Image &	image1,
		bool	insideIsPositive = `false`,
		bool	squaredDistance = `false`,
		bool	useImageSpacing = `false`
	)

itk::simple::SignedDanielssonDistanceMapImageFilter Procedural Interface

\ This function directly calls the execute method of SignedDanielssonDistanceMapImageFilter in order to support a procedural API

See also: itk::simple::SignedDanielssonDistanceMapImageFilter for the object oriented interface

◆ SignedMaurerDistanceMap()

Image itk::simple::SignedMaurerDistanceMap	(	const Image &	image1,
		bool	insideIsPositive = `false`,
		bool	squaredDistance = `true`,
		bool	useImageSpacing = `false`,
		double	backgroundValue = `0.0`
	)

This filter calculates the Euclidean distance transform of a binary image in linear time for arbitrary dimensions.

\ This function directly calls the execute method of SignedMaurerDistanceMapImageFilter in order to support a procedural API

See also: itk::simple::SignedMaurerDistanceMapImageFilter for the object oriented interface

◆ SimpleContourExtractor()

Image itk::simple::SimpleContourExtractor	(	const Image &	image1,
		double	inputForegroundValue = `1.0`,
		double	inputBackgroundValue = `0.0`,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`,
		double	outputForegroundValue = `1.0`,
		double	outputBackgroundValue = `0.0`
	)

Computes an image of contours which will be the contour of the first image.

\ This function directly calls the execute method of SimpleContourExtractorImageFilter in order to support a procedural API

See also: itk::simple::SimpleContourExtractorImageFilter for the object oriented interface

◆ Sin() [1/2]

Image itk::simple::Sin ( const Image & image1 )

Computes the sine of each pixel.

\ This function directly calls the execute method of SinImageFilter in order to support a procedural API

See also: itk::simple::SinImageFilter for the object oriented interface

◆ Sin() [2/2]

Image itk::simple::Sin ( Image && image1 )

Computes the sine of each pixel.

\ This function directly calls the execute method of SinImageFilter in order to support a procedural API

See also: itk::simple::SinImageFilter for the object oriented interface

◆ sitkITKDirectionToSTL()

template<typename TDirectionType >

std::vector<double> SITKCommon_HIDDEN itk::simple::sitkITKDirectionToSTL ( const TDirectionType & d )

Definition at line 199 of file sitkTemplateFunctions.h.

◆ sitkITKImageRegionToSTL()

template<unsigned int VImageDimension>

std::vector<unsigned int> SITKCommon_HIDDEN itk::simple::sitkITKImageRegionToSTL ( const ImageRegion< VImageDimension > & in )

Convert an ITK ImageRegion to and std::vector with the first part being the start index followed by the size.

Definition at line 160 of file sitkTemplateFunctions.h.

References itk::ImageRegion< VImageDimension >::GetIndex(), and itk::ImageRegion< VImageDimension >::GetSize().

◆ sitkITKVectorToSTL() [1/2]

template<typename TType , typename TITKVector >

std::vector<TType> SITKCommon_HIDDEN itk::simple::sitkITKVectorToSTL ( const std::vector< TITKVector > & in )

Definition at line 139 of file sitkTemplateFunctions.h.

◆ sitkITKVectorToSTL() [2/2]

template<typename TType , typename TITKVector >

std::vector<TType> SITKCommon_HIDDEN itk::simple::sitkITKVectorToSTL ( const TITKVector & in )

Convert an ITK fixed width vector to a std::vector.

Definition at line 109 of file sitkTemplateFunctions.h.

◆ sitkITKVersorToSTL()

template<typename TType , typename T >

std::vector<TType> SITKCommon_HIDDEN itk::simple::sitkITKVersorToSTL ( const itk::Versor< T > & in )

Definition at line 222 of file sitkTemplateFunctions.h.

References itk::Versor< T >::GetW(), itk::Versor< T >::GetX(), itk::Versor< T >::GetY(), and itk::Versor< T >::GetZ().

◆ sitkSTLToITKDirection()

template<typename TDirectionType >

TDirectionType SITKCommon_HIDDEN itk::simple::sitkSTLToITKDirection ( const std::vector< double > & direction )

Definition at line 177 of file sitkTemplateFunctions.h.

References sitkExceptionMacro.

◆ sitkSTLVectorToITK()

template<typename TITKVector , typename TType >

TITKVector SITKCommon_HIDDEN itk::simple::sitkSTLVectorToITK ( const std::vector< TType > & in )

Copy the elements of an std::vector into an ITK fixed width vector.

If there are more elements in parameter "in" than the templated ITK vector type, they are truncated. If less, then an exception is generated.

Definition at line 89 of file sitkTemplateFunctions.h.

References sitkExceptionMacro.

◆ sitkSTLVectorToITKPointVector()

template<typename TITKPointVector , typename TType >

TITKPointVector SITKCommon_HIDDEN itk::simple::sitkSTLVectorToITKPointVector ( const std::vector< TType > & in )

Definition at line 65 of file sitkTemplateFunctions.h.

References Dimension.

◆ sitkSTLVectorToITKVersor()

template<typename T , typename TType >

itk::Versor<T> SITKCommon_HIDDEN itk::simple::sitkSTLVectorToITKVersor ( const std::vector< TType > & in )

Definition at line 206 of file sitkTemplateFunctions.h.

References sitkExceptionMacro.

◆ sitkVectorOfITKVectorToSTL()

template<typename TType , typename TVectorOfITKVector >

std::vector<TType> SITKCommon_HIDDEN itk::simple::sitkVectorOfITKVectorToSTL ( const TVectorOfITKVector & in )

Convert an ITK style array of ITK fixed witdth vector to std::vector.

An example input type is itk::FixedArray<itk::Point<3>, 3>

Definition at line 124 of file sitkTemplateFunctions.h.

◆ SLIC()

Image itk::simple::SLIC	(	const Image &	image1,
		std::vector< unsigned int >	superGridSize = `std::vector< unsigned int >(3, 50)`,
		double	spatialProximityWeight = `10.0`,
		uint32_t	maximumNumberOfIterations = `5u`,
		bool	enforceConnectivity = `true`,
		bool	initializationPerturbation = `true`
	)

Simple Linear Iterative Clustering (SLIC) super-pixel segmentation.

\ This function directly calls the execute method of SLICImageFilter in order to support a procedural API

See also: itk::simple::SLICImageFilter for the object oriented interface

◆ Slice()

Image itk::simple::Slice	(	const Image &	image1,
		std::vector< int32_t >	start = `std::vector< int32_t >(3, 0)`,
		std::vector< int32_t >	stop = `std::vector< int32_t >(3, std::numeric_limits< int32_t >::max())`,
		std::vector< int >	step = `std::vector< int >(3, 1)`
	)

Slices an image based on a starting index and a stopping index, and a step size.

\ This function directly calls the execute method of SliceImageFilter in order to support a procedural API

See also: itk::simple::SliceImageFilter for the object oriented interface

◆ SmoothingRecursiveGaussian() [1/3]

Image itk::simple::SmoothingRecursiveGaussian	(	const Image &	image1,
		double	sigma,
		bool	normalizeAcrossScale = `false`
	)

Computes the smoothing of an image by convolution with the Gaussian kernels implemented as IIR filters.

This function directly calls the execute method of SmoothingRecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::SmoothingRecursiveGaussianImageFilter for the object oriented interface

Examples: SimpleGaussianFunctional.cxx.

◆ SmoothingRecursiveGaussian() [2/3]

Image itk::simple::SmoothingRecursiveGaussian	(	const Image &	image1,
		std::vector< double >	sigma = `std::vector< double >(3, 1.0)`,
		bool	normalizeAcrossScale = `false`
	)

Computes the smoothing of an image by convolution with the Gaussian kernels implemented as IIR filters.

\ This function directly calls the execute method of SmoothingRecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::SmoothingRecursiveGaussianImageFilter for the object oriented interface

◆ SmoothingRecursiveGaussian() [3/3]

Image itk::simple::SmoothingRecursiveGaussian	(	Image &&	image1,
		std::vector< double >	sigma = `std::vector< double >(3, 1.0)`,
		bool	normalizeAcrossScale = `false`
	)

Computes the smoothing of an image by convolution with the Gaussian kernels implemented as IIR filters.

\ This function directly calls the execute method of SmoothingRecursiveGaussianImageFilter in order to support a procedural API

See also: itk::simple::SmoothingRecursiveGaussianImageFilter for the object oriented interface

◆ SobelEdgeDetection()

Image itk::simple::SobelEdgeDetection ( const Image & image1 )

A 2D or 3D edge detection using the Sobel operator.

\ This function directly calls the execute method of SobelEdgeDetectionImageFilter in order to support a procedural API

See also: itk::simple::SobelEdgeDetectionImageFilter for the object oriented interface

◆ SpeckleNoise() [1/2]

Image itk::simple::SpeckleNoise	(	const Image &	image1,
		double	standardDeviation = `1.0`,
		uint32_t	seed = `(uint32_t) itk::simple::sitkWallClock`
	)

Alter an image with speckle (multiplicative) noise.

\ This function directly calls the execute method of SpeckleNoiseImageFilter in order to support a procedural API

See also: itk::simple::SpeckleNoiseImageFilter for the object oriented interface

◆ SpeckleNoise() [2/2]

Image itk::simple::SpeckleNoise	(	Image &&	image1,
		double	standardDeviation = `1.0`,
		uint32_t	seed = `(uint32_t) itk::simple::sitkWallClock`
	)

Alter an image with speckle (multiplicative) noise.

\ This function directly calls the execute method of SpeckleNoiseImageFilter in order to support a procedural API

See also: itk::simple::SpeckleNoiseImageFilter for the object oriented interface

◆ Sqrt() [1/2]

Image itk::simple::Sqrt ( const Image & image1 )

Computes the square root of each pixel.

\ This function directly calls the execute method of SqrtImageFilter in order to support a procedural API

See also: itk::simple::SqrtImageFilter for the object oriented interface

◆ Sqrt() [2/2]

Image itk::simple::Sqrt ( Image && image1 )

Computes the square root of each pixel.

\ This function directly calls the execute method of SqrtImageFilter in order to support a procedural API

See also: itk::simple::SqrtImageFilter for the object oriented interface

◆ Square() [1/2]

Image itk::simple::Square ( const Image & image1 )

Computes the square of the intensity values pixel-wise.

\ This function directly calls the execute method of SquareImageFilter in order to support a procedural API

See also: itk::simple::SquareImageFilter for the object oriented interface

◆ Square() [2/2]

Image itk::simple::Square ( Image && image1 )

Computes the square of the intensity values pixel-wise.

\ This function directly calls the execute method of SquareImageFilter in order to support a procedural API

See also: itk::simple::SquareImageFilter for the object oriented interface

◆ SquaredDifference() [1/5]

Image itk::simple::SquaredDifference	(	const Image &	image1,
		const Image &	image2
	)

Implements pixel-wise the computation of squared difference.

\ This function directly calls the execute method of SquaredDifferenceImageFilter in order to support a procedural API

See also: itk::simple::SquaredDifferenceImageFilter for the object oriented interface

◆ SquaredDifference() [2/5]

Image itk::simple::SquaredDifference	(	const Image &	image1,
		double	constant
	)

◆ SquaredDifference() [3/5]

Image itk::simple::SquaredDifference	(	double	constant,
		const Image &	image2
	)

◆ SquaredDifference() [4/5]

Image itk::simple::SquaredDifference	(	Image &&	image1,
		const Image &	image2
	)

Implements pixel-wise the computation of squared difference.

\ This function directly calls the execute method of SquaredDifferenceImageFilter in order to support a procedural API

See also: itk::simple::SquaredDifferenceImageFilter for the object oriented interface

◆ SquaredDifference() [5/5]

Image itk::simple::SquaredDifference	(	Image &&	image1,
		double	constant
	)

◆ StandardDeviationProjection()

Image itk::simple::StandardDeviationProjection	(	const Image &	image1,
		unsigned int	projectionDimension = `0u`
	)

Mean projection.

\ This function directly calls the execute method of StandardDeviationProjectionImageFilter in order to support a procedural API

See also: itk::simple::StandardDeviationProjectionImageFilter for the object oriented interface

◆ STAPLE() [1/6]

Image itk::simple::STAPLE	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5,
		double	confidenceWeight = `1.0`,
		double	foregroundValue = `1.0`,
		unsigned int	maximumIterations = `std::numeric_limits< unsigned int >::max()`
	)

The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations.

This function directly calls the execute method of STAPLEImageFilter in order to support a procedural API

See also: itk::simple::STAPLEImageFilter for the object oriented interface

◆ STAPLE() [2/6]

Image itk::simple::STAPLE	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		double	confidenceWeight = `1.0`,
		double	foregroundValue = `1.0`,
		unsigned int	maximumIterations = `std::numeric_limits< unsigned int >::max()`
	)

The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations.

This function directly calls the execute method of STAPLEImageFilter in order to support a procedural API

See also: itk::simple::STAPLEImageFilter for the object oriented interface

◆ STAPLE() [3/6]

Image itk::simple::STAPLE	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		double	confidenceWeight = `1.0`,
		double	foregroundValue = `1.0`,
		unsigned int	maximumIterations = `std::numeric_limits< unsigned int >::max()`
	)

The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations.

This function directly calls the execute method of STAPLEImageFilter in order to support a procedural API

See also: itk::simple::STAPLEImageFilter for the object oriented interface

◆ STAPLE() [4/6]

Image itk::simple::STAPLE	(	const Image &	image1,
		const Image &	image2,
		double	confidenceWeight = `1.0`,
		double	foregroundValue = `1.0`,
		unsigned int	maximumIterations = `std::numeric_limits< unsigned int >::max()`
	)

The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations.

This function directly calls the execute method of STAPLEImageFilter in order to support a procedural API

See also: itk::simple::STAPLEImageFilter for the object oriented interface

◆ STAPLE() [5/6]

Image itk::simple::STAPLE	(	const Image &	image1,
		double	confidenceWeight = `1.0`,
		double	foregroundValue = `1.0`,
		unsigned int	maximumIterations = `std::numeric_limits< unsigned int >::max()`
	)

The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations.

This function directly calls the execute method of STAPLEImageFilter in order to support a procedural API

See also: itk::simple::STAPLEImageFilter for the object oriented interface

◆ STAPLE() [6/6]

Image itk::simple::STAPLE	(	const std::vector< Image > &	images,
		double	confidenceWeight = `1.0`,
		double	foregroundValue = `1.0`,
		unsigned int	maximumIterations = `std::numeric_limits< unsigned int >::max()`
	)

The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations.

This function directly calls the execute method of STAPLEImageFilter in order to support a procedural API

See also: itk::simple::STAPLEImageFilter for the object oriented interface

◆ StochasticFractalDimension() [1/2]

Image itk::simple::StochasticFractalDimension	(	const Image &	image,
		const Image &	maskImage,
		std::vector< unsigned int >	neighborhoodRadius = `std::vector< unsigned int >(3, 2u)`
	)

This filter computes the stochastic fractal dimension of the input image.

\ This function directly calls the execute method of StochasticFractalDimensionImageFilter in order to support a procedural API

See also: itk::simple::StochasticFractalDimensionImageFilter for the object oriented interface

◆ StochasticFractalDimension() [2/2]

Image itk::simple::StochasticFractalDimension	(	const Image &	image,
		std::vector< unsigned int >	neighborhoodRadius = `std::vector< unsigned int >(3, 2u)`
	)

This filter computes the stochastic fractal dimension of the input image.

\ This function directly calls the execute method of StochasticFractalDimensionImageFilter in order to support a procedural API

See also: itk::simple::StochasticFractalDimensionImageFilter for the object oriented interface

◆ Subtract() [1/5]

Image itk::simple::Subtract	(	const Image &	image1,
		const Image &	image2
	)

Pixel-wise subtraction of two images.

\ This function directly calls the execute method of SubtractImageFilter in order to support a procedural API

See also: itk::simple::SubtractImageFilter for the object oriented interface

◆ Subtract() [2/5]

Image itk::simple::Subtract	(	const Image &	image1,
		double	constant
	)

◆ Subtract() [3/5]

Image itk::simple::Subtract	(	double	constant,
		const Image &	image2
	)

◆ Subtract() [4/5]

Image itk::simple::Subtract	(	Image &&	image1,
		const Image &	image2
	)

Pixel-wise subtraction of two images.

\ This function directly calls the execute method of SubtractImageFilter in order to support a procedural API

See also: itk::simple::SubtractImageFilter for the object oriented interface

Examples: CppInPlace/CppInPlace.cxx.

Referenced by operator-(), and operator-=().

◆ Subtract() [5/5]

Image itk::simple::Subtract	(	Image &&	image1,
		double	constant
	)

◆ SumProjection()

Image itk::simple::SumProjection	(	const Image &	image1,
		unsigned int	projectionDimension = `0u`
	)

Sum projection.

\ This function directly calls the execute method of SumProjectionImageFilter in order to support a procedural API

See also: itk::simple::SumProjectionImageFilter for the object oriented interface

◆ Tan() [1/2]

Image itk::simple::Tan ( const Image & image1 )

Computes the tangent of each input pixel.

\ This function directly calls the execute method of TanImageFilter in order to support a procedural API

See also: itk::simple::TanImageFilter for the object oriented interface

◆ Tan() [2/2]

Image itk::simple::Tan ( Image && image1 )

Computes the tangent of each input pixel.

\ This function directly calls the execute method of TanImageFilter in order to support a procedural API

See also: itk::simple::TanImageFilter for the object oriented interface

◆ TernaryAdd() [1/2]

Image itk::simple::TernaryAdd	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3
	)

Pixel-wise addition of three images.

\ This function directly calls the execute method of TernaryAddImageFilter in order to support a procedural API

See also: itk::simple::TernaryAddImageFilter for the object oriented interface

◆ TernaryAdd() [2/2]

Image itk::simple::TernaryAdd	(	Image &&	image1,
		const Image &	image2,
		const Image &	image3
	)

Pixel-wise addition of three images.

\ This function directly calls the execute method of TernaryAddImageFilter in order to support a procedural API

See also: itk::simple::TernaryAddImageFilter for the object oriented interface

◆ TernaryMagnitude() [1/2]

Image itk::simple::TernaryMagnitude	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3
	)

Compute the pixel-wise magnitude of three images.

\ This function directly calls the execute method of TernaryMagnitudeImageFilter in order to support a procedural API

See also: itk::simple::TernaryMagnitudeImageFilter for the object oriented interface

◆ TernaryMagnitude() [2/2]

Image itk::simple::TernaryMagnitude	(	Image &&	image1,
		const Image &	image2,
		const Image &	image3
	)

Compute the pixel-wise magnitude of three images.

\ This function directly calls the execute method of TernaryMagnitudeImageFilter in order to support a procedural API

See also: itk::simple::TernaryMagnitudeImageFilter for the object oriented interface

◆ TernaryMagnitudeSquared() [1/2]

Image itk::simple::TernaryMagnitudeSquared	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3
	)

Compute the pixel-wise squared magnitude of three images.

\ This function directly calls the execute method of TernaryMagnitudeSquaredImageFilter in order to support a procedural API

See also: itk::simple::TernaryMagnitudeSquaredImageFilter for the object oriented interface

◆ TernaryMagnitudeSquared() [2/2]

Image itk::simple::TernaryMagnitudeSquared	(	Image &&	image1,
		const Image &	image2,
		const Image &	image3
	)

Compute the pixel-wise squared magnitude of three images.

\ This function directly calls the execute method of TernaryMagnitudeSquaredImageFilter in order to support a procedural API

See also: itk::simple::TernaryMagnitudeSquaredImageFilter for the object oriented interface

◆ Threshold() [1/2]

Image itk::simple::Threshold	(	const Image &	image1,
		double	lower = `0.0`,
		double	upper = `1.0`,
		double	outsideValue = `0.0`
	)

Set image values to a user-specified value if they are below, above, or between simple threshold values.

\ This function directly calls the execute method of ThresholdImageFilter in order to support a procedural API

See also: itk::simple::ThresholdImageFilter for the object oriented interface

◆ Threshold() [2/2]

Image itk::simple::Threshold	(	Image &&	image1,
		double	lower = `0.0`,
		double	upper = `1.0`,
		double	outsideValue = `0.0`
	)

Set image values to a user-specified value if they are below, above, or between simple threshold values.

\ This function directly calls the execute method of ThresholdImageFilter in order to support a procedural API

See also: itk::simple::ThresholdImageFilter for the object oriented interface

Referenced by itk::simple::IsolatedWatershedImageFilter::SetThreshold(), itk::simple::UnsharpMaskImageFilter::SetThreshold(), itk::simple::BinaryMinMaxCurvatureFlowImageFilter::SetThreshold(), and itk::simple::CannySegmentationLevelSetImageFilter::SetThreshold().

◆ ThresholdMaximumConnectedComponents()

Image itk::simple::ThresholdMaximumConnectedComponents	(	const Image &	image1,
		uint32_t	minimumObjectSizeInPixels = `0u`,
		double	upperBoundary = `std::numeric_limits< double >::max()`,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`
	)

Finds the threshold value of an image based on maximizing the number of objects in the image that are larger than a given minimal size.

\ This function directly calls the execute method of ThresholdMaximumConnectedComponentsImageFilter in order to support a procedural API

See also: itk::simple::ThresholdMaximumConnectedComponentsImageFilter for the object oriented interface

◆ ThresholdSegmentationLevelSet() [1/2]

Image itk::simple::ThresholdSegmentationLevelSet	(	const Image &	initialImage,
		const Image &	featureImage,
		double	lowerThreshold = `0.0`,
		double	upperThreshold = `255.0`,
		double	maximumRMSError = `0.02`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`
	)

Segments structures in images based on intensity values.

\ This function directly calls the execute method of ThresholdSegmentationLevelSetImageFilter in order to support a procedural API

See also: itk::simple::ThresholdSegmentationLevelSetImageFilter for the object oriented interface

◆ ThresholdSegmentationLevelSet() [2/2]

Image itk::simple::ThresholdSegmentationLevelSet	(	Image &&	initialImage,
		const Image &	featureImage,
		double	lowerThreshold = `0.0`,
		double	upperThreshold = `255.0`,
		double	maximumRMSError = `0.02`,
		double	propagationScaling = `1.0`,
		double	curvatureScaling = `1.0`,
		uint32_t	numberOfIterations = `1000u`,
		bool	reverseExpansionDirection = `false`
	)

Segments structures in images based on intensity values.

\ This function directly calls the execute method of ThresholdSegmentationLevelSetImageFilter in order to support a procedural API

See also: itk::simple::ThresholdSegmentationLevelSetImageFilter for the object oriented interface

◆ TikhonovDeconvolution()

Image itk::simple::TikhonovDeconvolution	(	const Image &	image1,
		const Image &	image2,
		double	regularizationConstant = `0.0`,
		bool	normalize = `false`,
		TikhonovDeconvolutionImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::TikhonovDeconvolutionImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		TikhonovDeconvolutionImageFilter::OutputRegionModeType	outputRegionMode = `itk::simple::TikhonovDeconvolutionImageFilter::SAME`
	)

An inverse deconvolution filter regularized in the Tikhonov sense.

\ This function directly calls the execute method of TikhonovDeconvolutionImageFilter in order to support a procedural API

See also: itk::simple::TikhonovDeconvolutionImageFilter for the object oriented interface

◆ Tile() [1/6]

Image itk::simple::Tile	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		const Image &	image5,
		std::vector< uint32_t >	layout = `std::vector< uint32_t >(3, 100)`,
		double	defaultPixelValue = `0.0`
	)

Tile multiple input images into a single output image.

This function directly calls the execute method of TileImageFilter in order to support a procedural API

See also: itk::simple::TileImageFilter for the object oriented interface

◆ Tile() [2/6]

Image itk::simple::Tile	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		const Image &	image4,
		std::vector< uint32_t >	layout = `std::vector< uint32_t >(3, 100)`,
		double	defaultPixelValue = `0.0`
	)

Tile multiple input images into a single output image.

This function directly calls the execute method of TileImageFilter in order to support a procedural API

See also: itk::simple::TileImageFilter for the object oriented interface

◆ Tile() [3/6]

Image itk::simple::Tile	(	const Image &	image1,
		const Image &	image2,
		const Image &	image3,
		std::vector< uint32_t >	layout = `std::vector< uint32_t >(3, 100)`,
		double	defaultPixelValue = `0.0`
	)

Tile multiple input images into a single output image.

This function directly calls the execute method of TileImageFilter in order to support a procedural API

See also: itk::simple::TileImageFilter for the object oriented interface

◆ Tile() [4/6]

Image itk::simple::Tile	(	const Image &	image1,
		const Image &	image2,
		std::vector< uint32_t >	layout = `std::vector< uint32_t >(3, 100)`,
		double	defaultPixelValue = `0.0`
	)

Tile multiple input images into a single output image.

This function directly calls the execute method of TileImageFilter in order to support a procedural API

See also: itk::simple::TileImageFilter for the object oriented interface

◆ Tile() [5/6]

Image itk::simple::Tile	(	const Image &	image1,
		std::vector< uint32_t >	layout = `std::vector< uint32_t >(3, 100)`,
		double	defaultPixelValue = `0.0`
	)

Tile multiple input images into a single output image.

This function directly calls the execute method of TileImageFilter in order to support a procedural API

See also: itk::simple::TileImageFilter for the object oriented interface

◆ Tile() [6/6]

Image itk::simple::Tile	(	const std::vector< Image > &	images,
		std::vector< uint32_t >	layout = `std::vector< uint32_t >(3, 100)`,
		double	defaultPixelValue = `0.0`
	)

Tile multiple input images into a single output image.

This function directly calls the execute method of TileImageFilter in order to support a procedural API

See also: itk::simple::TileImageFilter for the object oriented interface

◆ Toboggan()

Image itk::simple::Toboggan ( const Image & image1 )

toboggan image segmentation The Toboggan segmentation takes a gradient magnitude image as input and produces an (over-)segmentation of the image based on connecting each pixel to a local minimum of gradient. It is roughly equivalent to a watershed segmentation of the lowest level.

\ This function directly calls the execute method of TobogganImageFilter in order to support a procedural API

See also: itk::simple::TobogganImageFilter for the object oriented interface

◆ TransformToDisplacementField()

Image itk::simple::TransformToDisplacementField	(	const Transform &	transform,
		PixelIDValueEnum	outputPixelType = `itk::simple::sitkVectorFloat64`,
		std::vector< unsigned int >	size = `std::vector< unsigned int >(3, 64)`,
		std::vector< double >	outputOrigin = `std::vector< double >(3, 0.0)`,
		std::vector< double >	outputSpacing = `std::vector< double >(3, 1.0)`,
		std::vector< double >	outputDirection = `std::vector< double >()`
	)

Generate a displacement field from a coordinate transform.

This function directly calls the execute method of TransformToDisplacementFieldFilter in order to support a procedural API

See also: itk::simple::TransformToDisplacementFieldFilter for the object oriented interface

◆ TriangleThreshold() [1/2]

Image itk::simple::TriangleThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Triangle Threshold.

\ This function directly calls the execute method of TriangleThresholdImageFilter in order to support a procedural API

See also: itk::simple::TriangleThresholdImageFilter for the object oriented interface

◆ TriangleThreshold() [2/2]

Image itk::simple::TriangleThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Triangle Threshold.

\ This function directly calls the execute method of TriangleThresholdImageFilter in order to support a procedural API

See also: itk::simple::TriangleThresholdImageFilter for the object oriented interface

◆ UnaryMinus() [1/2]

Image itk::simple::UnaryMinus ( const Image & image1 )

Implements pixel-wise generic operation on one image.

\ This function directly calls the execute method of UnaryMinusImageFilter in order to support a procedural API

See also: itk::simple::UnaryMinusImageFilter for the object oriented interface

◆ UnaryMinus() [2/2]

Image itk::simple::UnaryMinus ( Image && image1 )

Implements pixel-wise generic operation on one image.

\ This function directly calls the execute method of UnaryMinusImageFilter in order to support a procedural API

See also: itk::simple::UnaryMinusImageFilter for the object oriented interface

Referenced by operator-().

◆ UnsharpMask()

Image itk::simple::UnsharpMask	(	const Image &	image1,
		std::vector< double >	sigmas = `std::vector< double >(3, 1.0)`,
		double	amount = `0.5`,
		double	threshold = `0.0`
	)

Edge enhancement filter.

\ This function directly calls the execute method of UnsharpMaskImageFilter in order to support a procedural API

See also: itk::simple::UnsharpMaskImageFilter for the object oriented interface

◆ Unused()

template<typename T >

void SITKCommon_HIDDEN itk::simple::Unused ( const T & )

A function which does nothing.

This function is to be used to mark parameters as unused to suppress compiler warning.

Definition at line 42 of file sitkTemplateFunctions.h.

◆ ValuedRegionalMaxima()

Image itk::simple::ValuedRegionalMaxima	(	const Image &	image1,
		bool	fullyConnected = `false`
	)

Transforms the image so that any pixel that is not a regional maxima is set to the minimum value for the pixel type. Pixels that are regional maxima retain their value.

\ This function directly calls the execute method of ValuedRegionalMaximaImageFilter in order to support a procedural API

See also: itk::simple::ValuedRegionalMaximaImageFilter for the object oriented interface

◆ ValuedRegionalMinima()

Image itk::simple::ValuedRegionalMinima	(	const Image &	image1,
		bool	fullyConnected = `false`
	)

Transforms the image so that any pixel that is not a regional minima is set to the maximum value for the pixel type. Pixels that are regional minima retain their value.

\ This function directly calls the execute method of ValuedRegionalMinimaImageFilter in order to support a procedural API

See also: itk::simple::ValuedRegionalMinimaImageFilter for the object oriented interface

◆ VectorConfidenceConnected()

Image itk::simple::VectorConfidenceConnected	(	const Image &	image1,
		std::vector< std::vector< unsigned int > >	seedList = `std::vector< std::vector< unsigned int > >()`,
		unsigned int	numberOfIterations = `4u`,
		double	multiplier = `4.5`,
		unsigned int	initialNeighborhoodRadius = `1u`,
		uint8_t	replaceValue = `1u`
	)

Segment pixels with similar statistics using connectivity.

\ This function directly calls the execute method of VectorConfidenceConnectedImageFilter in order to support a procedural API

See also: itk::simple::VectorConfidenceConnectedImageFilter for the object oriented interface

◆ VectorConnectedComponent()

Image itk::simple::VectorConnectedComponent	(	const Image &	image1,
		double	distanceThreshold = `1.0`,
		bool	fullyConnected = `false`
	)

A connected components filter that labels the objects in a vector image. Two vectors are pointing similar directions if one minus their dot product is less than a threshold. Vectors that are 180 degrees out of phase are similar. Assumes that vectors are normalized.

\ This function directly calls the execute method of VectorConnectedComponentImageFilter in order to support a procedural API

See also: itk::simple::VectorConnectedComponentImageFilter for the object oriented interface

◆ VectorIndexSelectionCast() [1/2]

Image itk::simple::VectorIndexSelectionCast	(	const Image &	image1,
		unsigned int	index = `0u`,
		PixelIDValueEnum	outputPixelType = `itk::simple::sitkUnknown`
	)

Extracts the selected index of the vector that is the input pixel type.

\ This function directly calls the execute method of VectorIndexSelectionCastImageFilter in order to support a procedural API

See also: itk::simple::VectorIndexSelectionCastImageFilter for the object oriented interface

◆ VectorIndexSelectionCast() [2/2]

Image itk::simple::VectorIndexSelectionCast	(	Image &&	image1,
		unsigned int	index = `0u`,
		PixelIDValueEnum	outputPixelType = `itk::simple::sitkUnknown`
	)

Extracts the selected index of the vector that is the input pixel type.

\ This function directly calls the execute method of VectorIndexSelectionCastImageFilter in order to support a procedural API

See also: itk::simple::VectorIndexSelectionCastImageFilter for the object oriented interface

◆ VectorMagnitude() [1/2]

Image itk::simple::VectorMagnitude ( const Image & image1 )

Take an image of vectors as input and produce an image with the magnitude of those vectors.

\ This function directly calls the execute method of VectorMagnitudeImageFilter in order to support a procedural API

See also: itk::simple::VectorMagnitudeImageFilter for the object oriented interface

◆ VectorMagnitude() [2/2]

Image itk::simple::VectorMagnitude ( Image && image1 )

Take an image of vectors as input and produce an image with the magnitude of those vectors.

\ This function directly calls the execute method of VectorMagnitudeImageFilter in order to support a procedural API

See also: itk::simple::VectorMagnitudeImageFilter for the object oriented interface

◆ VotingBinary()

Image itk::simple::VotingBinary	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`,
		unsigned int	birthThreshold = `1u`,
		unsigned int	survivalThreshold = `1u`,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0.0`
	)

Applies a voting operation in a neighborhood of each pixel.

\ This function directly calls the execute method of VotingBinaryImageFilter in order to support a procedural API

See also: itk::simple::VotingBinaryImageFilter for the object oriented interface

◆ VotingBinaryHoleFilling()

Image itk::simple::VotingBinaryHoleFilling	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`,
		unsigned int	majorityThreshold = `1u`,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0.0`
	)

Fills in holes and cavities by applying a voting operation on each pixel.

\ This function directly calls the execute method of VotingBinaryHoleFillingImageFilter in order to support a procedural API

See also: itk::simple::VotingBinaryHoleFillingImageFilter for the object oriented interface

◆ VotingBinaryIterativeHoleFilling()

Image itk::simple::VotingBinaryIterativeHoleFilling	(	const Image &	image1,
		std::vector< unsigned int >	radius = `std::vector< unsigned int >(3, 1)`,
		unsigned int	maximumNumberOfIterations = `10u`,
		unsigned int	majorityThreshold = `1u`,
		double	foregroundValue = `1.0`,
		double	backgroundValue = `0.0`
	)

Fills in holes and cavities by iteratively applying a voting operation.

\ This function directly calls the execute method of VotingBinaryIterativeHoleFillingImageFilter in order to support a procedural API

See also: itk::simple::VotingBinaryIterativeHoleFillingImageFilter for the object oriented interface

◆ Warp()

Image itk::simple::Warp	(	const Image &	image,
		const Image &	displacementField,
		InterpolatorEnum	interpolator = `itk::simple::sitkLinear`,
		std::vector< uint32_t >	outputSize = `std::vector< uint32_t >(3, 0)`,
		std::vector< double >	outputOrigin = `std::vector< double >(3, 0.0)`,
		std::vector< double >	outputSpacing = `std::vector< double >(3, 1.0)`,
		std::vector< double >	outputDirection = `std::vector< double >()`,
		double	edgePaddingValue = `0.0`
	)

Warps an image using an input displacement field.

\ This function directly calls the execute method of WarpImageFilter in order to support a procedural API

See also: itk::simple::WarpImageFilter for the object oriented interface

◆ WhiteTopHat()

Image itk::simple::WhiteTopHat	(	const Image &	image1,
		std::vector< unsigned int >	kernelRadius = `std::vector< uint32_t >(3, 1)`,
		KernelEnum	kernelType = `itk::simple::sitkBall`,
		bool	safeBorder = `true`
	)

White top hat extracts local maxima that are larger than the structuring element.

\ This function directly calls the execute method of WhiteTopHatImageFilter in order to support a procedural API

See also: itk::simple::WhiteTopHatImageFilter for the object oriented interface

◆ WienerDeconvolution()

Image itk::simple::WienerDeconvolution	(	const Image &	image1,
		const Image &	image2,
		double	noiseVariance = `0.0`,
		bool	normalize = `false`,
		WienerDeconvolutionImageFilter::BoundaryConditionType	boundaryCondition = `itk::simple::WienerDeconvolutionImageFilter::ZERO_FLUX_NEUMANN_PAD`,
		WienerDeconvolutionImageFilter::OutputRegionModeType	outputRegionMode = `itk::simple::WienerDeconvolutionImageFilter::SAME`
	)

The Wiener deconvolution image filter is designed to restore an image convolved with a blurring kernel while keeping noise enhancement to a minimum.

\ This function directly calls the execute method of WienerDeconvolutionImageFilter in order to support a procedural API

See also: itk::simple::WienerDeconvolutionImageFilter for the object oriented interface

◆ WrapPad()

Image itk::simple::WrapPad	(	const Image &	image1,
		std::vector< unsigned int >	padLowerBound = `std::vector< unsigned int >(3, 0)`,
		std::vector< unsigned int >	padUpperBound = `std::vector< unsigned int >(3, 0)`
	)

Increase the image size by padding with replicants of the input image value.

\ This function directly calls the execute method of WrapPadImageFilter in order to support a procedural API

See also: itk::simple::WrapPadImageFilter for the object oriented interface

◆ WriteImage() [1/2]

SITKIO_EXPORT void itk::simple::WriteImage	(	const Image &	image,
		const std::string &	fileName,
		bool	useCompression = `false`,
		int	compressionLevel = `-1`
	)

WriteImage is a procedural interface to the ImageFileWriter. class which is convenient for many image writing tasks.

Parameters

image	the input image to be written
fileName	the filename of an Image e.g. "cthead.mha"
useCompression	request to compress the written file
compressionLevel	a hint for the amount of compression to be applied during writing

See also: itk::simple::ImageFileWriter for writing a single file.

Examples: CppCMake/Source/sitk_example.cxx, CppInPlace/CppInPlace.cxx, DicomSeriesReader/DicomSeriesReader.cxx, FastMarchingSegmentation/FastMarchingSegmentation.cxx, SimpleGaussianFunctional.cxx, and SliceBySliceDecorator/SliceBySliceDecorator.cxx.

◆ WriteImage() [2/2]

SITKIO_EXPORT void itk::simple::WriteImage	(	const Image &	image,
		const std::vector< std::string > &	fileNames,
		bool	useCompression = `false`,
		int	compressionLevel = `-1`
	)

WriteImage is a procedural interface to the ImageSeriesWriter. class which is convenient for many image writing tasks.

Parameters

image	the input image to be written
fileNames	a vector of filenames of length equal to the number of slices in the image.
useCompression	request to compress the written file
compressionLevel	a hint for the amount of compression to be applied during writing.

See also: itk::simple::ImageFileWriter for writing a single file.

◆ WriteTransform()

SITKCommon_EXPORT void itk::simple::WriteTransform	(	const Transform &	transform,
		const std::string &	filename
	)

Examples: DemonsRegistration1/DemonsRegistration1.cxx, DemonsRegistration2/DemonsRegistration2.cxx, ImageRegistrationMethod1/ImageRegistrationMethod1.cxx, ImageRegistrationMethod2/ImageRegistrationMethod2.cxx, ImageRegistrationMethodBSpline1/ImageRegistrationMethodBSpline1.cxx, ImageRegistrationMethodBSpline3/ImageRegistrationMethodBSpline3.cxx, and ImageRegistrationMethodDisplacement1/ImageRegistrationMethodDisplacement1.cxx.

◆ Xor() [1/5]

Image itk::simple::Xor	(	const Image &	image1,
		const Image &	image2
	)

Computes the XOR bitwise operator pixel-wise between two images.

\ This function directly calls the execute method of XorImageFilter in order to support a procedural API

See also: itk::simple::XorImageFilter for the object oriented interface

◆ Xor() [2/5]

Image itk::simple::Xor	(	const Image &	image1,
		int	constant
	)

◆ Xor() [3/5]

Image itk::simple::Xor	(	Image &&	image1,
		const Image &	image2
	)

Computes the XOR bitwise operator pixel-wise between two images.

\ This function directly calls the execute method of XorImageFilter in order to support a procedural API

See also: itk::simple::XorImageFilter for the object oriented interface

Referenced by operator^(), and operator^=().

◆ Xor() [4/5]

Image itk::simple::Xor	(	Image &&	image1,
		int	constant
	)

◆ Xor() [5/5]

Image itk::simple::Xor	(	int	constant,
		const Image &	image2
	)

◆ YenThreshold() [1/2]

Image itk::simple::YenThreshold	(	const Image &	image,
		const Image &	maskImage,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Yen Threshold.

\ This function directly calls the execute method of YenThresholdImageFilter in order to support a procedural API

See also: itk::simple::YenThresholdImageFilter for the object oriented interface

◆ YenThreshold() [2/2]

Image itk::simple::YenThreshold	(	const Image &	image,
		uint8_t	insideValue = `1u`,
		uint8_t	outsideValue = `0u`,
		uint32_t	numberOfHistogramBins = `256u`,
		bool	maskOutput = `true`,
		uint8_t	maskValue = `255u`
	)

Threshold an image using the Yen Threshold.

\ This function directly calls the execute method of YenThresholdImageFilter in order to support a procedural API

See also: itk::simple::YenThresholdImageFilter for the object oriented interface

◆ ZeroCrossing()

Image itk::simple::ZeroCrossing	(	const Image &	image1,
		uint8_t	foregroundValue = `1u`,
		uint8_t	backgroundValue = `0u`
	)

This filter finds the closest pixel to the zero-crossings (sign changes) in a signed itk::Image .

\ This function directly calls the execute method of ZeroCrossingImageFilter in order to support a procedural API

See also: itk::simple::ZeroCrossingImageFilter for the object oriented interface

◆ ZeroCrossingBasedEdgeDetection()

Image itk::simple::ZeroCrossingBasedEdgeDetection	(	const Image &	image1,
		double	variance = `1.0`,
		uint8_t	foregroundValue = `1u`,
		uint8_t	backgroundValue = `0u`,
		double	maximumError = `0.1`
	)

This filter implements a zero-crossing based edge detecor.

\ This function directly calls the execute method of ZeroCrossingBasedEdgeDetectionImageFilter in order to support a procedural API

See also: itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter for the object oriented interface

◆ ZeroFluxNeumannPad()

Image itk::simple::ZeroFluxNeumannPad	(	const Image &	image1,
		std::vector< unsigned int >	padLowerBound = `std::vector< unsigned int >(3, 0)`,
		std::vector< unsigned int >	padUpperBound = `std::vector< unsigned int >(3, 0)`
	)

Increase the image size by padding according to the zero-flux Neumann boundary condition.

\ This function directly calls the execute method of ZeroFluxNeumannPadImageFilter in order to support a procedural API

See also: itk::simple::ZeroFluxNeumannPadImageFilter for the object oriented interface

Namespaces

Classes

Typedefs

Enumerations

Functions

Typedef Documentation

◆ AllPixelIDTypeList

◆ BasicPixelIDTypeList

◆ ComplexPixelIDTypeList

◆ FalseType

◆ InstantiatedPixelIDTypeList

◆ IntegerLabelPixelIDTypeList

◆ IntegerPixelIDTypeList

◆ LabelPixelIDTypeList

◆ NonLabelPixelIDTypeList

◆ PixelIDValueType

◆ RealPixelIDTypeList

◆ RealVectorPixelIDTypeList

◆ ScalarPixelIDTypeList

◆ SignedPixelIDTypeList

◆ SignedVectorPixelIDTypeList

◆ TrueType

◆ UnsignedIntegerPixelIDTypeList

◆ VectorPixelIDTypeList

Enumeration Type Documentation

◆ EventEnum

◆ InterpolatorEnum

◆ KernelEnum

◆ PixelIDValueEnum

◆ SeedEnum

◆ TransformEnum

Function Documentation

◆ Abs() [1/2]

◆ Abs() [2/2]

◆ AbsoluteValueDifference() [1/5]

◆ AbsoluteValueDifference() [2/5]

◆ AbsoluteValueDifference() [3/5]

◆ AbsoluteValueDifference() [4/5]

◆ AbsoluteValueDifference() [5/5]

◆ Acos() [1/2]

◆ Acos() [2/2]

◆ AdaptiveHistogramEqualization()

◆ Add() [1/5]

◆ Add() [2/5]

◆ Add() [3/5]

◆ Add() [4/5]

◆ Add() [5/5]

◆ AdditiveGaussianNoise() [1/2]

◆ AdditiveGaussianNoise() [2/2]

◆ AggregateLabelMap() [1/2]

◆ AggregateLabelMap() [2/2]

◆ And() [1/5]

◆ And() [2/5]

◆ And() [3/5]

◆ And() [4/5]

◆ And() [5/5]

◆ AntiAliasBinary() [1/2]

◆ AntiAliasBinary() [2/2]

◆ ApproximateSignedDistanceMap()

◆ Asin() [1/2]

◆ Asin() [2/2]

◆ Atan() [1/2]

◆ Atan() [2/2]

◆ Atan2() [1/5]

◆ Atan2() [2/5]

◆ Atan2() [3/5]

◆ Atan2() [4/5]

◆ Atan2() [5/5]

◆ Bilateral()

◆ BinaryClosingByReconstruction()

◆ BinaryContour() [1/2]

◆ BinaryContour() [2/2]

◆ BinaryDilate()

◆ BinaryErode()

◆ BinaryFillhole()

◆ BinaryGrindPeak()

◆ BinaryImageToLabelMap()

◆ BinaryMagnitude() [1/2]

◆ BinaryMagnitude() [2/2]

◆ BinaryMedian()