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

#include <sitkN4BiasFieldCorrectionImageFilter.h>

Inheritance diagram for itk::simple::N4BiasFieldCorrectionImageFilter:

Collaboration diagram for itk::simple::N4BiasFieldCorrectionImageFilter:

Public Types
using	PixelIDTypeList = RealPixelIDTypeList

using	Self = N4BiasFieldCorrectionImageFilter

Public Types inherited from itk::simple::ImageFilter
using	Self = ImageFilter

Public Types inherited from itk::simple::ProcessObject
using	Self = ProcessObject

Public Member Functions
Image	Execute (const Image &image)

Image	Execute (const Image &image, const Image &maskImage)

double	GetBiasFieldFullWidthAtHalfMaximum () const

double	GetConvergenceThreshold () const

uint8_t	GetMaskLabel () const

std::vector< uint32_t >	GetMaximumNumberOfIterations () const

std::string	GetName () const

std::vector< uint32_t >	GetNumberOfControlPoints () const

uint32_t	GetNumberOfHistogramBins () const

uint32_t	GetSplineOrder () const

bool	GetUseMaskLabel () const

double	GetWienerFilterNoise () const

	N4BiasFieldCorrectionImageFilter ()

Self &	SetBiasFieldFullWidthAtHalfMaximum (double BiasFieldFullWidthAtHalfMaximum)

Self &	SetConvergenceThreshold (double ConvergenceThreshold)

Self &	SetMaskLabel (uint8_t MaskLabel)

Self &	SetMaximumNumberOfIterations (std::vector< uint32_t > MaximumNumberOfIterations)

Self &	SetNumberOfControlPoints (std::vector< uint32_t > NumberOfControlPoints)

Self &	SetNumberOfControlPoints (uint32_t value)

Self &	SetNumberOfHistogramBins (uint32_t NumberOfHistogramBins)

Self &	SetSplineOrder (uint32_t SplineOrder)

Self &	SetUseMaskLabel (bool UseMaskLabel)

Self &	SetWienerFilterNoise (double WienerFilterNoise)

std::string	ToString () const

Self &	UseMaskLabelOff ()

Self &	UseMaskLabelOn ()

virtual	~N4BiasFieldCorrectionImageFilter ()

Public Member Functions inherited from itk::simple::ImageFilter
	ImageFilter ()

virtual	~ImageFilter ()=0

Public Member Functions inherited from itk::simple::ProcessObject
virtual void	Abort ()

virtual int	AddCommand (itk::simple::EventEnum event, const std::function< void()> &func)
	Directly add a callback to observe an event. More...

virtual int	AddCommand (itk::simple::EventEnum event, itk::simple::Command &cmd)
	Add a Command Object to observer the event. More...

virtual float	GetProgress () const
	An Active Measurement of the progress of execution. More...

virtual bool	HasCommand (itk::simple::EventEnum event) const
	Query of this object has any registered commands for event. More...

	ProcessObject ()

virtual void	RemoveAllCommands ()
	Remove all registered commands. More...

virtual	~ProcessObject ()

virtual void	DebugOn ()

virtual void	DebugOff ()

virtual bool	GetDebug () const

virtual void	SetDebug (bool debugFlag)

virtual void	SetNumberOfThreads (unsigned int n)

virtual unsigned int	GetNumberOfThreads () const

virtual void	SetNumberOfWorkUnits (unsigned int n)

virtual unsigned int	GetNumberOfWorkUnits () const

Private Types
using	MemberFunctionType = Image(Self::)(const Image image, const Image *maskImage)

Private Member Functions
template<class TImageType >
Image	ExecuteInternal (const Image image, const Image maskImage)

Private Attributes
double	m_BiasFieldFullWidthAtHalfMaximum {0.15}

double	m_ConvergenceThreshold {0.001}

uint8_t	m_MaskLabel {1}

std::vector< uint32_t >	m_MaximumNumberOfIterations {std::vector<uint32_t>(4,50)}

std::unique_ptr< detail::MemberFunctionFactory< MemberFunctionType > >	m_MemberFactory

std::vector< uint32_t >	m_NumberOfControlPoints {std::vector<uint32_t>(3, 4)}

uint32_t	m_NumberOfHistogramBins {200u}

uint32_t	m_SplineOrder {3u}

bool	m_UseMaskLabel {true}

double	m_WienerFilterNoise {0.01}

Friends
struct	detail::MemberFunctionAddressor< MemberFunctionType >

Additional Inherited Members
Static Public Member Functions inherited from itk::simple::ProcessObject
static bool	GetGlobalDefaultDebug ()

static void	GlobalDefaultDebugOff ()

static void	GlobalDefaultDebugOn ()

static void	SetGlobalDefaultDebug (bool debugFlag)

static void	GlobalWarningDisplayOn ()

static void	GlobalWarningDisplayOff ()

static void	SetGlobalWarningDisplay (bool flag)

static bool	GetGlobalWarningDisplay ()

static double	GetGlobalDefaultCoordinateTolerance ()
	Access the global tolerance to determine congruent spaces. More...

static void	SetGlobalDefaultCoordinateTolerance (double)
	Access the global tolerance to determine congruent spaces. More...

static double	GetGlobalDefaultDirectionTolerance ()
	Access the global tolerance to determine congruent spaces. More...

static void	SetGlobalDefaultDirectionTolerance (double)
	Access the global tolerance to determine congruent spaces. More...

static bool	SetGlobalDefaultThreader (const std::string &threader)
	Set/Get the default threader used for process objects. More...

static std::string	GetGlobalDefaultThreader ()
	Set/Get the default threader used for process objects. More...

static void	SetGlobalDefaultNumberOfThreads (unsigned int n)

static unsigned int	GetGlobalDefaultNumberOfThreads ()
	Set/Get the default threader used for process objects. More...

Protected Member Functions inherited from itk::simple::ImageFilter
void	CheckImageMatchingDimension (const Image &image1, const Image &image2, const std::string &image2Name)

void	CheckImageMatchingPixelType (const Image &image1, const Image &image2, const std::string &image2Name)

void	CheckImageMatchingSize (const Image &image1, const Image &image2, const std::string &image2Name)

Protected Member Functions inherited from itk::simple::ProcessObject
virtual unsigned long	AddITKObserver (const itk::EventObject &, itk::Command *)

virtual itk::ProcessObject *	GetActiveProcess ()

virtual void	OnActiveProcessDelete ()

virtual void	onCommandDelete (const itk::simple::Command *cmd) noexcept

virtual void	PreUpdate (itk::ProcessObject *p)

virtual void	RemoveITKObserver (EventCommand &e)

Protected Member Functions inherited from itk::simple::NonCopyable
	NonCopyable ()=default

	NonCopyable (const NonCopyable &)=delete

NonCopyable &	operator= (const NonCopyable &)=delete

Static Protected Member Functions inherited from itk::simple::ImageFilter
template<class TImageType >
static void	FixNonZeroIndex (TImageType *img)

Static Protected Member Functions inherited from itk::simple::ProcessObject
template<class TImageType >
static TImageType::ConstPointer	CastImageToITK (const Image &img)

template<class TPixelType , unsigned int VImageDimension, unsigned int VLength, template< typename, unsigned int > class TVector>
static Image	CastITKToImage (itk::Image< TVector< TPixelType, VLength >, VImageDimension > *img)

template<class TImageType >
static Image	CastITKToImage (TImageType *img)

static const itk::EventObject &	GetITKEventObject (EventEnum e)

template<typename T >
static std::ostream &	ToStringHelper (std::ostream &os, const T &v)

static std::ostream &	ToStringHelper (std::ostream &os, const char &v)

static std::ostream &	ToStringHelper (std::ostream &os, const signed char &v)

static std::ostream &	ToStringHelper (std::ostream &os, const unsigned char &v)

Detailed Description

Implementation of the N4 bias field correction algorithm.

The nonparametric nonuniform intensity normalization (N3) algorithm, as introduced by Sled et al. in 1998 is a method for correcting nonuniformity associated with MR images. The algorithm assumes a simple parametric model (Gaussian) for the bias field and does not require tissue class segmentation. In addition, there are only a couple of parameters to tune with the default values performing quite well. N3 has been publicly available as a set of perl scripts (http://www.bic.mni.mcgill.ca/ServicesSoftwareAdvancedImageProcessingTools/HomePage )

The N4 algorithm, encapsulated with this class, is a variation of the original N3 algorithm with the additional benefits of an improved B-spline fitting routine which allows for multiple resolutions to be used during the correction process. We also modify the iterative update component of algorithm such that the residual bias field is continually updated

Notes for the user:

Since much of the image manipulation is done in the log space of the intensities, input images with negative and small values (< 1) can produce poor results.

The original authors recommend performing the bias field correction on a downsampled version of the original image.

A binary mask or a weighted image can be supplied. If a binary mask is specified, those voxels in the input image which correspond to the voxels in the mask image are used to estimate the bias field. If a UseMaskLabel value is set to false (the default), all non-zero voxels in the MaskImage will be masked; otherwise only voxels in the MaskImage that match the MaskLabel will be used. If a confidence image is specified, the input voxels are weighted in the b-spline fitting routine according to the confidence voxel values.

The filter returns the corrected image. If the bias field is wanted, one can reconstruct it using the class itkBSplineControlPointImageFilter. See the IJ article and the test file for an example.

The 'Z' parameter in Sled's 1998 paper is the square root of the class variable 'm_WienerFilterNoise'.

The basic algorithm iterates between sharpening the intensity histogram of the corrected input image and spatially smoothing those results with a B-spline scalar field estimate of the bias field.

Author: Nicholas J. Tustison

Contributed by Nicholas J. Tustison, James C. Gee in the Insight Journal paper: https://hdl.handle.net/10380/3053

REFERENCE

J.G. Sled, A.P. Zijdenbos and A.C. Evans. "A Nonparametric Method for Automatic Correction of Intensity Nonuniformity in Data" IEEE Transactions on Medical Imaging, Vol 17, No 1. Feb 1998.

N.J. Tustison, B.B. Avants, P.A. Cook, Y. Zheng, A. Egan, P.A. Yushkevich, and J.C. Gee. "N4ITK: Improved N3 Bias Correction" IEEE Transactions on Medical Imaging, 29(6):1310-1320, June 2010.

See also: itk::simple::N4BiasFieldCorrection for the procedural interface; itk::N4BiasFieldCorrectionImageFilter for the Doxygen on the original ITK class.

Definition at line 74 of file sitkN4BiasFieldCorrectionImageFilter.h.

Member Typedef Documentation

◆ MemberFunctionType

using itk::simple::N4BiasFieldCorrectionImageFilter::MemberFunctionType = Image (Self::*)( const Image * image, const Image * maskImage )

private

Setup for member function dispatching

Definition at line 202 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ PixelIDTypeList

using itk::simple::N4BiasFieldCorrectionImageFilter::PixelIDTypeList = RealPixelIDTypeList

Define the pixels types supported by this filter

Definition at line 86 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ Self

using itk::simple::N4BiasFieldCorrectionImageFilter::Self = N4BiasFieldCorrectionImageFilter

Definition at line 76 of file sitkN4BiasFieldCorrectionImageFilter.h.

Constructor & Destructor Documentation

◆ ~N4BiasFieldCorrectionImageFilter()

virtual itk::simple::N4BiasFieldCorrectionImageFilter::~N4BiasFieldCorrectionImageFilter ( )

virtual

Destructor

◆ N4BiasFieldCorrectionImageFilter()

itk::simple::N4BiasFieldCorrectionImageFilter::N4BiasFieldCorrectionImageFilter ( )

Default Constructor that takes no arguments and initializes default parameters

Member Function Documentation

◆ Execute() [1/2]

Image itk::simple::N4BiasFieldCorrectionImageFilter::Execute ( const Image & image )

◆ Execute() [2/2]

Image itk::simple::N4BiasFieldCorrectionImageFilter::Execute	(	const Image &	image,
		const Image &	maskImage
	)

Execute the filter on the input image

◆ ExecuteInternal()

template<class TImageType >

Image itk::simple::N4BiasFieldCorrectionImageFilter::ExecuteInternal	(	const Image *	image,
		const Image *	maskImage
	)

private

◆ GetBiasFieldFullWidthAtHalfMaximum()

double itk::simple::N4BiasFieldCorrectionImageFilter::GetBiasFieldFullWidthAtHalfMaximum ( ) const

inline

Get the full width at half maximum parameter characterizing the width of the Gaussian deconvolution. Default = 0.15.

Definition at line 117 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetConvergenceThreshold()

double itk::simple::N4BiasFieldCorrectionImageFilter::GetConvergenceThreshold ( ) const

inline

Get the convergence threshold. Convergence is determined by the coefficient of variation of the difference image between the current bias field estimate and the previous estimate. If this value is less than the specified threshold, the algorithm proceeds to the next fitting level or terminates if it is at the last level.

Definition at line 97 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetMaskLabel()

uint8_t itk::simple::N4BiasFieldCorrectionImageFilter::GetMaskLabel ( ) const

inline

DeprecatedSet/Get mask label value. If a binary mask image is specified and if UseMaskValue is true, only those input image voxels corresponding with mask image values equal to MaskLabel are used in estimating the bias field. If a MaskImage is specified and UseMaskLabel is false, all input image voxels corresponding to non-zero voxels in the MaskImage are used in estimating the bias field. Default = 1.

Definition at line 184 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetMaximumNumberOfIterations()

std::vector<uint32_t> itk::simple::N4BiasFieldCorrectionImageFilter::GetMaximumNumberOfIterations ( ) const

inline

Get the maximum number of iterations specified at each fitting level. Default = 50.

Definition at line 107 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetName()

std::string itk::simple::N4BiasFieldCorrectionImageFilter::GetName ( ) const

inlinevirtual

Name of this class

Implements itk::simple::ProcessObject.

Definition at line 187 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetNumberOfControlPoints()

std::vector<uint32_t> itk::simple::N4BiasFieldCorrectionImageFilter::GetNumberOfControlPoints ( ) const

inline

Get the control point grid size defining the B-spline estimate of the scalar bias field. In each dimension, the B-spline mesh size is equal to the number of control points in that dimension minus the spline order. Default = 4 control points in each dimension for a mesh size of 1 in each dimension.

Definition at line 150 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetNumberOfHistogramBins()

uint32_t itk::simple::N4BiasFieldCorrectionImageFilter::GetNumberOfHistogramBins ( ) const

inline

Get number of bins defining the log input intensity histogram. Default = 200.

Definition at line 137 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetSplineOrder()

uint32_t itk::simple::N4BiasFieldCorrectionImageFilter::GetSplineOrder ( ) const

inline

Get the spline order defining the bias field estimate. Default = 3.

Definition at line 160 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetUseMaskLabel()

bool itk::simple::N4BiasFieldCorrectionImageFilter::GetUseMaskLabel ( ) const

inline

Use a mask label for identifying mask functionality. See SetMaskLabel. Defaults to true.

Definition at line 174 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ GetWienerFilterNoise()

double itk::simple::N4BiasFieldCorrectionImageFilter::GetWienerFilterNoise ( ) const

inline

Get the noise estimate defining the Wiener filter. Default = 0.01.

Definition at line 127 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ SetBiasFieldFullWidthAtHalfMaximum()

Self& itk::simple::N4BiasFieldCorrectionImageFilter::SetBiasFieldFullWidthAtHalfMaximum ( double BiasFieldFullWidthAtHalfMaximum )

inline

Set the full width at half maximum parameter characterizing the width of the Gaussian deconvolution. Default = 0.15.

Definition at line 112 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ SetConvergenceThreshold()

Self& itk::simple::N4BiasFieldCorrectionImageFilter::SetConvergenceThreshold ( double ConvergenceThreshold )

inline

Set the convergence threshold. Convergence is determined by the coefficient of variation of the difference image between the current bias field estimate and the previous estimate. If this value is less than the specified threshold, the algorithm proceeds to the next fitting level or terminates if it is at the last level.

Definition at line 92 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ SetMaskLabel()

Self& itk::simple::N4BiasFieldCorrectionImageFilter::SetMaskLabel ( uint8_t MaskLabel )

inline

Set/Get mask label value. If a binary mask image is specified and if UseMaskValue is true, only those input image voxels corresponding with mask image values equal to MaskLabel are used in estimating the bias field. If a MaskImage is specified and UseMaskLabel is false, all input image voxels corresponding to non-zero voxels in the MaskImage are used in estimating the bias field. Default = 1.

Definition at line 179 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ SetMaximumNumberOfIterations()

Self& itk::simple::N4BiasFieldCorrectionImageFilter::SetMaximumNumberOfIterations ( std::vector< uint32_t > MaximumNumberOfIterations )

inline

Set the maximum number of iterations specified at each fitting level. Default = 50.

Definition at line 102 of file sitkN4BiasFieldCorrectionImageFilter.h.

◆ SetNumberOfControlPoints() [1/2]

Self& itk::simple::N4BiasFieldCorrectionImageFilter::SetNumberOfControlPoints ( std::vector< uint32_t > NumberOfControlPoints )

inline

Set the control point grid size defining the B-spline estimate of the scalar bias field. In each dimension, the B-spline mesh size is equal to the number of control points in that dimension minus the spline order. Default = 4 control points in each dimension for a mesh size of 1 in each dimension.

Definition at line 142 of file sitkN4BiasFieldCorrectionImageFilter.h.