SimpleITK  2.0.0
Namespaces | Classes | Typedefs | Enumerations | Functions
itk::simple Namespace Reference

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

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

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

Definition at line 167 of file sitkPixelIDTypeLists.h.

◆ 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

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

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

See also
BasicPixelID

Definition at line 59 of file sitkPixelIDTypeLists.h.

◆ SignedPixelIDTypeList

List of pixel ids which are signed

See also
BasicPixelID

Definition at line 116 of file sitkPixelIDTypeLists.h.

◆ 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

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

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

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

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

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

Definition at line 29 of file sitkKernel.h.

◆ 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 )
{
// handle exceptional case
break
...
break;
...
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

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

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_titk::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_titk::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 
)

◆ 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 
)

◆ 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)

◆ 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 
)

◆ 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)

◆ 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() [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
fileNamesa vector of file names
outputPixelTypesee ImageReaderBase::SetOutputPixelType
imageIOsee 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)

◆ 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_titk::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_titk::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_titk::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_titk::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)

◆ 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_titk::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_titk::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
imagethe input image to be written
fileNamethe filename of an Image e.g. "cthead.mha"
useCompressionrequest to compress the written file
compressionLevela 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
imagethe input image to be written
fileNamesa vector of filenames of length equal to the number of slices in the image.
useCompressionrequest to compress the written file
compressionLevela 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 
)

◆ 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
itk::simple::sitkInt8
@ sitkInt8
Signed 8 bit integer.
Definition: sitkPixelIDValues.h:93
itk::simple::sitkUInt8
@ sitkUInt8
Unsigned 8 bit integer.
Definition: sitkPixelIDValues.h:92
itk::simple::ConditionalValue
Definition: sitkConditional.h:38
itk::simple::sitkUnknown
@ sitkUnknown
Definition: sitkPixelIDValues.h:91