itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage > Class Template Reference

#include <itkN4BiasFieldCorrectionImageFilter.h>

Inheritance diagram for itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >:

Collaboration diagram for itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >:

Public Types
using	ArrayType = typename BSplineFilterType::ArrayType
using	BiasFieldControlPointLatticeType = typename BSplineFilterType::PointDataImageType
using	BSplineFilterType = BSplineScatteredDataPointSetToImageFilter< PointSetType, ScalarImageType >
using	ConstPointer = SmartPointer< const Self >
using	InputImageType = TInputImage
using	MaskImageType = TMaskImage
using	MaskPixelType = typename MaskImageType::PixelType
using	OutputImageType = TOutputImage
using	Pointer = SmartPointer< Self >
using	PointSetPointer = typename PointSetType::Pointer
using	PointSetType = PointSet< ScalarType, Self::ImageDimension >
using	PointType = typename PointSetType::PointType
using	RealImagePointer = typename RealImageType::Pointer
using	RealImageType = Image< RealType, ImageDimension >
using	RealType = float
using	ScalarImageType = Image< ScalarType, Self::ImageDimension >
using	ScalarType = Vector< RealType, 1 >
using	Self = N4BiasFieldCorrectionImageFilter
using	Superclass = ImageToImageFilter< TInputImage, TOutputImage >
using	VariableSizeArrayType = Array< unsigned int >
Public Types inherited from itk::ImageToImageFilter< TInputImage, TOutputImage >
using	ConstPointer = SmartPointer< const Self >
using	InputImageConstPointer = typename InputImageType::ConstPointer
using	InputImagePixelType = typename InputImageType::PixelType
using	InputImagePointer = typename InputImageType::Pointer
using	InputImageRegionType = typename InputImageType::RegionType
using	InputImageType = TInputImage
using	OutputImagePixelType = typename Superclass::OutputImagePixelType
using	OutputImageRegionType = typename Superclass::OutputImageRegionType
using	Pointer = SmartPointer< Self >
using	Self = ImageToImageFilter
using	Superclass = ImageSource< TOutputImage >
Public Types inherited from itk::ImageSource< TOutputImage >
using	ConstPointer = SmartPointer< const Self >
using	DataObjectIdentifierType = Superclass::DataObjectIdentifierType
using	DataObjectPointer = DataObject::Pointer
using	DataObjectPointerArraySizeType = Superclass::DataObjectPointerArraySizeType
using	OutputImagePixelType = typename OutputImageType::PixelType
using	OutputImagePointer = typename OutputImageType::Pointer
using	OutputImageRegionType = typename OutputImageType::RegionType
using	OutputImageType = TOutputImage
using	Pointer = SmartPointer< Self >
using	Self = ImageSource
using	Superclass = ProcessObject
Public Types inherited from itk::ProcessObject
using	ConstPointer = SmartPointer< const Self >
using	DataObjectIdentifierType = DataObject::DataObjectIdentifierType
using	DataObjectPointer = DataObject::Pointer
using	DataObjectPointerArray = std::vector< DataObjectPointer >
using	DataObjectPointerArraySizeType = DataObjectPointerArray::size_type
using	MultiThreaderType = MultiThreaderBase
using	NameArray = std::vector< DataObjectIdentifierType >
using	Pointer = SmartPointer< Self >
using	Self = ProcessObject
using	Superclass = Object
Public Types inherited from itk::Object
using	ConstPointer = SmartPointer< const Self >
using	Pointer = SmartPointer< Self >
using	Self = Object
using	Superclass = LightObject
Public Types inherited from itk::LightObject
using	ConstPointer = SmartPointer< const Self >
using	Pointer = SmartPointer< Self >
using	Self = LightObject

Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother () const
void	EnlargeOutputRequestedRegion (DataObject *) override
virtual const char *	GetNameOfClass () const
void	SetInput1 (const InputImageType *image)
Public Member Functions inherited from itk::ImageToImageFilter< TInputImage, TOutputImage >
const InputImageType *	GetInput () const
const InputImageType *	GetInput (unsigned int idx) const
void	PopBackInput () override
void	PopFrontInput () override
virtual void	PushBackInput (const InputImageType *input)
virtual void	PushFrontInput (const InputImageType *input)
virtual void	SetInput (const DataObjectIdentifierType &key, DataObject *input)
virtual void	SetInput (const InputImageType *input)
virtual void	SetInput (unsigned int, const TInputImage *image)
virtual void	SetCoordinateTolerance (double _arg)
virtual double	GetCoordinateTolerance () const
virtual void	SetDirectionTolerance (double _arg)
virtual double	GetDirectionTolerance () const
Public Member Functions inherited from itk::ImageSource< TOutputImage >
OutputImageType *	GetOutput ()
const OutputImageType *	GetOutput () const
OutputImageType *	GetOutput (unsigned int idx)
virtual void	GraftOutput (DataObject *graft)
virtual void	GraftOutput (const DataObjectIdentifierType &key, DataObject *graft)
virtual void	GraftNthOutput (unsigned int idx, DataObject *graft)
ProcessObject::DataObjectPointer	MakeOutput (ProcessObject::DataObjectPointerArraySizeType idx) override
ProcessObject::DataObjectPointer	MakeOutput (const ProcessObject::DataObjectIdentifierType &) override
Public Member Functions inherited from itk::ProcessObject
virtual void	AbortGenerateDataOff ()
virtual void	AbortGenerateDataOn ()
virtual const bool &	GetAbortGenerateData () const
DataObjectPointerArray	GetIndexedInputs ()
DataObjectPointerArray	GetIndexedOutputs ()
NameArray	GetInputNames () const
DataObjectPointerArray	GetInputs ()
DataObjectPointerArraySizeType	GetNumberOfIndexedInputs () const
DataObjectPointerArraySizeType	GetNumberOfIndexedOutputs () const
DataObjectPointerArraySizeType	GetNumberOfInputs () const
DataObjectPointerArraySizeType	GetNumberOfOutputs () const
virtual DataObjectPointerArraySizeType	GetNumberOfValidRequiredInputs () const
NameArray	GetOutputNames () const
DataObjectPointerArray	GetOutputs ()
virtual float	GetProgress () const
NameArray	GetRequiredInputNames () const
bool	HasInput (const DataObjectIdentifierType &key) const
bool	HasOutput (const DataObjectIdentifierType &key) const
void	IncrementProgress (float increment)
virtual void	PropagateRequestedRegion (DataObject *output)
virtual void	ResetPipeline ()
virtual void	SetAbortGenerateData (bool _arg)
virtual void	Update ()
virtual void	UpdateLargestPossibleRegion ()
virtual void	UpdateOutputData (DataObject *output)
virtual void	UpdateOutputInformation ()
void	UpdateProgress (float progress)
virtual void	SetReleaseDataFlag (bool val)
virtual bool	GetReleaseDataFlag () const
void	ReleaseDataFlagOn ()
void	ReleaseDataFlagOff ()
virtual void	SetReleaseDataBeforeUpdateFlag (bool _arg)
virtual const bool &	GetReleaseDataBeforeUpdateFlag () const
virtual void	ReleaseDataBeforeUpdateFlagOn ()
virtual void	ReleaseDataBeforeUpdateFlagOff ()
virtual void	SetNumberOfWorkUnits (ThreadIdType _arg)
virtual const ThreadIdType &	GetNumberOfWorkUnits () const
MultiThreaderType *	GetMultiThreader () const
void	SetMultiThreader (MultiThreaderType *threader)
virtual void	PrepareOutputs ()
Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)
unsigned long	AddObserver (const EventObject &event, Command *) const
unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const
virtual void	DebugOff () const
virtual void	DebugOn () const
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
MetaDataDictionary &	GetMetaDataDictionary ()
const MetaDataDictionary &	GetMetaDataDictionary () const
virtual ModifiedTimeType	GetMTime () const
virtual const TimeStamp &	GetTimeStamp () const
bool	HasObserver (const EventObject &event) const
void	InvokeEvent (const EventObject &)
void	InvokeEvent (const EventObject &) const
virtual void	Modified () const
void	Register () const override
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
void	SetDebug (bool debugFlag) const
void	SetReferenceCount (int) override
void	UnRegister () const noexcept override
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)
virtual void	SetObjectName (std::string _arg)
virtual const std::string &	GetObjectName () const
Public Member Functions inherited from itk::LightObject
Pointer	Clone () const
virtual void	Delete ()
virtual int	GetReferenceCount () const
void	Print (std::ostream &os, Indent indent=0) const

Static Public Member Functions
static Pointer	New ()
Static Public Member Functions inherited from itk::ImageToImageFilter< TInputImage, TOutputImage >
static void	SetGlobalDefaultDirectionTolerance (double)
static double	GetGlobalDefaultDirectionTolerance ()
static void	SetGlobalDefaultCoordinateTolerance (double)
static double	GetGlobalDefaultCoordinateTolerance ()
Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static Pointer	New ()
static void	SetGlobalWarningDisplay (bool val)
Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()
static Pointer	New ()

Static Public Attributes
static constexpr unsigned int	ImageDimension = TInputImage::ImageDimension
Static Public Attributes inherited from itk::ImageToImageFilter< TInputImage, TOutputImage >
static constexpr unsigned int	InputImageDimension = TInputImage::ImageDimension
static constexpr unsigned int	OutputImageDimension = TOutputImage::ImageDimension
Static Public Attributes inherited from itk::ImageSource< TOutputImage >
static constexpr unsigned int	OutputImageDimension = TOutputImage::ImageDimension
MaskPixelType	m_MaskLabel
bool	m_UseMaskLabel { false }
unsigned int	m_NumberOfHistogramBins { 200 }
RealType	m_WienerFilterNoise { static_cast<RealType>(0.01) }
RealType	m_BiasFieldFullWidthAtHalfMaximum { static_cast<RealType>(0.15) }
VariableSizeArrayType	m_MaximumNumberOfIterations
unsigned int	m_ElapsedIterations { 0 }
RealType	m_ConvergenceThreshold { static_cast<RealType>(0.001) }
RealType	m_CurrentConvergenceMeasurement
unsigned int	m_CurrentLevel { 0 }
BiasFieldControlPointLatticeType::Pointer	m_LogBiasFieldControlPointLattice
unsigned int	m_SplineOrder { 3 }
ArrayType	m_NumberOfControlPoints
ArrayType	m_NumberOfFittingLevels
virtual void	SetMaskImage (const MaskImageType *input)
void	SetInput2 (const MaskImageType *mask)
virtual const MaskImageType *	GetMaskImage () const
virtual void	SetMaskLabel (MaskPixelType _arg)
virtual MaskPixelType	GetMaskLabel () const
virtual void	SetUseMaskLabel (bool _arg)
virtual bool	GetUseMaskLabel () const
virtual void	UseMaskLabelOn ()
virtual void	UseMaskLabelOff ()
virtual void	SetConfidenceImage (const RealImageType *input)
void	SetInput3 (const RealImageType *image)
virtual const RealImageType *	GetConfidenceImage () const
virtual void	SetNumberOfHistogramBins (unsigned int _arg)
virtual unsigned int	GetNumberOfHistogramBins () const
virtual void	SetWienerFilterNoise (RealType _arg)
virtual RealType	GetWienerFilterNoise () const
virtual void	SetBiasFieldFullWidthAtHalfMaximum (RealType _arg)
virtual RealType	GetBiasFieldFullWidthAtHalfMaximum () const
virtual void	SetSplineOrder (unsigned int _arg)
virtual unsigned int	GetSplineOrder () const
virtual void	SetNumberOfControlPoints (ArrayType _arg)
virtual ArrayType	GetNumberOfControlPoints () const
virtual void	SetNumberOfFittingLevels (ArrayType _arg)
void	SetNumberOfFittingLevels (unsigned int n)
virtual ArrayType	GetNumberOfFittingLevels () const
virtual void	SetMaximumNumberOfIterations (VariableSizeArrayType _arg)
virtual VariableSizeArrayType	GetMaximumNumberOfIterations () const
virtual void	SetConvergenceThreshold (RealType _arg)
virtual RealType	GetConvergenceThreshold () const
virtual const BiasFieldControlPointLatticeType *	GetLogBiasFieldControlPointLattice () const
virtual unsigned int	GetElapsedIterations () const
virtual RealType	GetCurrentConvergenceMeasurement () const
virtual unsigned int	GetCurrentLevel () const
RealImagePointer	ReconstructBiasField (const BiasFieldControlPointLatticeType *)
	N4BiasFieldCorrectionImageFilter ()
	~N4BiasFieldCorrectionImageFilter () override=default
void	PrintSelf (std::ostream &os, Indent indent) const override
void	GenerateData () override
void	SharpenImage (const RealImageType *unsharpenedImage, RealImageType *sharpenedImage) const
RealImagePointer	UpdateBiasFieldEstimate (RealImageType *, std::vcl_size_t)
RealType	CalculateConvergenceMeasurement (const RealImageType *, const RealImageType *) const

Additional Inherited Members
Protected Types inherited from itk::ImageToImageFilter< TInputImage, TOutputImage >
using	InputToOutputRegionCopierType = ImageToImageFilterDetail::ImageRegionCopier< Self::OutputImageDimension, Self::InputImageDimension >
using	OutputToInputRegionCopierType = ImageToImageFilterDetail::ImageRegionCopier< Self::InputImageDimension, Self::OutputImageDimension >
Protected Member Functions inherited from itk::ImageToImageFilter< TInputImage, TOutputImage >
	ImageToImageFilter ()
	~ImageToImageFilter () override=default
void	VerifyInputInformation () ITKv5_CONST override
void	GenerateInputRequestedRegion () override
virtual void	CallCopyOutputRegionToInputRegion (InputImageRegionType &destRegion, const OutputImageRegionType &srcRegion)
virtual void	CallCopyInputRegionToOutputRegion (OutputImageRegionType &destRegion, const InputImageRegionType &srcRegion)
void	PushBackInput (const DataObject *input) override
void	PushFrontInput (const DataObject *input) override
Protected Member Functions inherited from itk::ImageSource< TOutputImage >
	ImageSource ()
	~ImageSource () override=default
void	ClassicMultiThread (ThreadFunctionType callbackFunction)
virtual void	ThreadedGenerateData (const OutputImageRegionType &region, ThreadIdType threadId)
virtual void	DynamicThreadedGenerateData (const OutputImageRegionType &outputRegionForThread)
virtual void	AllocateOutputs ()
virtual void	BeforeThreadedGenerateData ()
virtual void	AfterThreadedGenerateData ()
virtual const ImageRegionSplitterBase *	GetImageRegionSplitter () const
virtual unsigned int	SplitRequestedRegion (unsigned int i, unsigned int pieces, OutputImageRegionType &splitRegion)
virtual bool	GetDynamicMultiThreading () const
virtual void	SetDynamicMultiThreading (bool _arg)
virtual void	DynamicMultiThreadingOn ()
virtual void	DynamicMultiThreadingOff ()
Protected Member Functions inherited from itk::ProcessObject
	ProcessObject ()
	~ProcessObject () override
DataObject *	GetInput (const DataObjectIdentifierType &key)
const DataObject *	GetInput (const DataObjectIdentifierType &key) const
DataObject *	GetInput (DataObjectPointerArraySizeType idx)
const DataObject *	GetInput (DataObjectPointerArraySizeType idx) const
virtual void	SetInput (const DataObjectIdentifierType &key, DataObject *input)
virtual void	SetNthInput (DataObjectPointerArraySizeType idx, DataObject *input)
virtual void	AddInput (DataObject *input)
virtual void	RemoveInput (const DataObjectIdentifierType &key)
virtual void	RemoveInput (DataObjectPointerArraySizeType)
DataObject *	GetPrimaryInput ()
const DataObject *	GetPrimaryInput () const
virtual void	SetPrimaryInputName (const DataObjectIdentifierType &key)
virtual const char *	GetPrimaryInputName () const
virtual void	SetPrimaryInput (DataObject *object)
void	SetNumberOfIndexedInputs (DataObjectPointerArraySizeType num)
virtual void	SetNumberOfRequiredInputs (DataObjectPointerArraySizeType)
virtual const DataObjectPointerArraySizeType &	GetNumberOfRequiredInputs () const
bool	RemoveRequiredInputName (const DataObjectIdentifierType &)
bool	IsRequiredInputName (const DataObjectIdentifierType &) const
void	SetRequiredInputNames (const NameArray &)
bool	AddRequiredInputName (const DataObjectIdentifierType &)
bool	AddRequiredInputName (const DataObjectIdentifierType &, DataObjectPointerArraySizeType idx)
void	AddOptionalInputName (const DataObjectIdentifierType &)
void	AddOptionalInputName (const DataObjectIdentifierType &, DataObjectPointerArraySizeType idx)
DataObject *	GetOutput (const DataObjectIdentifierType &key)
const DataObject *	GetOutput (const DataObjectIdentifierType &key) const
virtual void	SetPrimaryOutputName (const DataObjectIdentifierType &key)
virtual const char *	GetPrimaryOutputName () const
DataObject *	GetOutput (DataObjectPointerArraySizeType i)
const DataObject *	GetOutput (DataObjectPointerArraySizeType i) const
virtual void	SetOutput (const DataObjectIdentifierType &name, DataObject *output)
virtual void	RemoveOutput (const DataObjectIdentifierType &key)
DataObject *	GetPrimaryOutput ()
const DataObject *	GetPrimaryOutput () const
virtual void	SetPrimaryOutput (DataObject *object)
virtual void	SetNthOutput (DataObjectPointerArraySizeType idx, DataObject *output)
virtual void	AddOutput (DataObject *output)
virtual void	RemoveOutput (DataObjectPointerArraySizeType idx)
virtual void	SetNumberOfRequiredOutputs (DataObjectPointerArraySizeType _arg)
virtual const DataObjectPointerArraySizeType &	GetNumberOfRequiredOutputs () const
void	SetNumberOfIndexedOutputs (DataObjectPointerArraySizeType num)
DataObjectIdentifierType	MakeNameFromInputIndex (DataObjectPointerArraySizeType idx) const
DataObjectIdentifierType	MakeNameFromOutputIndex (DataObjectPointerArraySizeType idx) const
DataObjectPointerArraySizeType	MakeIndexFromInputName (const DataObjectIdentifierType &name) const
DataObjectPointerArraySizeType	MakeIndexFromOutputName (const DataObjectIdentifierType &name) const
bool	IsIndexedInputName (const DataObjectIdentifierType &) const
bool	IsIndexedOutputName (const DataObjectIdentifierType &) const
virtual void	VerifyPreconditions () ITKv5_CONST
virtual void	GenerateOutputRequestedRegion (DataObject *output)
virtual void	GenerateOutputInformation ()
virtual void	PropagateResetPipeline ()
virtual void	ReleaseInputs ()
virtual void	CacheInputReleaseDataFlags ()
virtual void	RestoreInputReleaseDataFlags ()
virtual bool	GetThreaderUpdateProgress () const
virtual void	ThreaderUpdateProgressOn ()
virtual void	ThreaderUpdateProgressOff ()
virtual void	SetThreaderUpdateProgress (bool arg)
Protected Member Functions inherited from itk::Object
	Object ()
	~Object () override
bool	PrintObservers (std::ostream &os, Indent indent) const
virtual void	SetTimeStamp (const TimeStamp &timeStamp)
Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer	InternalClone () const
	LightObject ()
virtual void	PrintHeader (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const
virtual	~LightObject ()
Static Protected Member Functions inherited from itk::ImageSource< TOutputImage >
static const ImageRegionSplitterBase *	GetGlobalDefaultSplitter ()
static ITK_THREAD_RETURN_FUNCTION_CALL_CONVENTION	ThreaderCallback (void *arg)
Static Protected Member Functions inherited from itk::ProcessObject
static constexpr float	progressFixedToFloat (uint32_t fixed)
static uint32_t	progressFloatToFixed (float f)
Protected Attributes inherited from itk::ImageSource< TOutputImage >
bool	m_DynamicMultiThreading
Protected Attributes inherited from itk::ProcessObject
bool	m_Updating
TimeStamp	m_OutputInformationMTime
Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount

Detailed Description

template<typename TInputImage, typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>
class itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >

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:

1. 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.
2. The original authors recommend performing the bias field correction on a downsampled version of the original image.
3. 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.
4. 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.
5. 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://www.insight-journal.org/browse/publication/640

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.

Definition at line 96 of file itkN4BiasFieldCorrectionImageFilter.h.

Member Typedef Documentation

ArrayType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::ArrayType = typename BSplineFilterType::ArrayType

Definition at line 137 of file itkN4BiasFieldCorrectionImageFilter.h.

BiasFieldControlPointLatticeType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::BiasFieldControlPointLatticeType = typename BSplineFilterType::PointDataImageType

Definition at line 136 of file itkN4BiasFieldCorrectionImageFilter.h.

BSplineFilterType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::BSplineFilterType = BSplineScatteredDataPointSetToImageFilter<PointSetType, ScalarImageType>

B-sline filter type alias

Definition at line 135 of file itkN4BiasFieldCorrectionImageFilter.h.

ConstPointer

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::ConstPointer = SmartPointer<const Self>

Definition at line 105 of file itkN4BiasFieldCorrectionImageFilter.h.

InputImageType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::InputImageType = TInputImage

Some convenient type alias.

Definition at line 117 of file itkN4BiasFieldCorrectionImageFilter.h.

MaskImageType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::MaskImageType = TMaskImage

Definition at line 119 of file itkN4BiasFieldCorrectionImageFilter.h.

MaskPixelType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::MaskPixelType = typename MaskImageType::PixelType

Definition at line 120 of file itkN4BiasFieldCorrectionImageFilter.h.

OutputImageType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::OutputImageType = TOutputImage

Definition at line 118 of file itkN4BiasFieldCorrectionImageFilter.h.

Pointer

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::Pointer = SmartPointer<Self>

Definition at line 104 of file itkN4BiasFieldCorrectionImageFilter.h.

PointSetPointer

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::PointSetPointer = typename PointSetType::Pointer

Definition at line 131 of file itkN4BiasFieldCorrectionImageFilter.h.

PointSetType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::PointSetType = PointSet<ScalarType, Self::ImageDimension>

Definition at line 129 of file itkN4BiasFieldCorrectionImageFilter.h.

PointType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::PointType = typename PointSetType::PointType

Definition at line 132 of file itkN4BiasFieldCorrectionImageFilter.h.

RealImagePointer

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::RealImagePointer = typename RealImageType::Pointer

Definition at line 124 of file itkN4BiasFieldCorrectionImageFilter.h.

RealImageType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::RealImageType = Image<RealType, ImageDimension>

Definition at line 123 of file itkN4BiasFieldCorrectionImageFilter.h.

RealType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::RealType = float

Definition at line 122 of file itkN4BiasFieldCorrectionImageFilter.h.

ScalarImageType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::ScalarImageType = Image<ScalarType, Self::ImageDimension>

Definition at line 130 of file itkN4BiasFieldCorrectionImageFilter.h.

ScalarType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::ScalarType = Vector<RealType, 1>

B-spline smoothing filter argument type alias

Definition at line 128 of file itkN4BiasFieldCorrectionImageFilter.h.

Self

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::Self = N4BiasFieldCorrectionImageFilter

Standard class type aliases.

Definition at line 102 of file itkN4BiasFieldCorrectionImageFilter.h.

Superclass

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::Superclass = ImageToImageFilter<TInputImage, TOutputImage>

Definition at line 103 of file itkN4BiasFieldCorrectionImageFilter.h.

VariableSizeArrayType

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

using itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::VariableSizeArrayType = Array<unsigned int>

Definition at line 125 of file itkN4BiasFieldCorrectionImageFilter.h.

Constructor & Destructor Documentation

N4BiasFieldCorrectionImageFilter()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::N4BiasFieldCorrectionImageFilter ( )

protected

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

~N4BiasFieldCorrectionImageFilter()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::~N4BiasFieldCorrectionImageFilter ( )

overrideprotecteddefault

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Member Function Documentation

CalculateConvergenceMeasurement()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::CalculateConvergenceMeasurement ( const RealImageType *  , const RealImageType *    ) const

private

Convergence is determined by the coefficient of variation of the difference image between the current bias field estimate and the previous estimate.

CreateAnother()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual::itk::LightObject::Pointer itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::CreateAnother ( ) const

virtual

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::Object.

EnlargeOutputRequestedRegion()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::EnlargeOutputRequestedRegion ( DataObject *  )

overridevirtual

Ensures that this filter can compute the entire output at once.

Reimplemented from itk::ProcessObject.

GenerateData()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GenerateData ( )

overrideprotectedvirtual

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Reimplemented from itk::ImageSource< TOutputImage >.

GetBiasFieldFullWidthAtHalfMaximum()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetBiasFieldFullWidthAtHalfMaximum ( ) const

virtual

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

GetConfidenceImage()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual const RealImageType* itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetConfidenceImage ( ) const

virtual

Get confidence image function. If a confidence image is specified, estimation of the bias field weights the contribution of each voxel according the value of the corresponding voxel in the confidence image. For example, when estimating the bias field using brain , one can use a soft segmentation of the white matter as the confidence image instead of using a hard segmentation of the white matter as the mask image (as has been done in the literature) as an alternative strategy to estimating the bias field.

GetConvergenceThreshold()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetConvergenceThreshold ( ) const

virtual

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.

GetCurrentConvergenceMeasurement()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetCurrentConvergenceMeasurement ( ) const

virtual

Get the current convergence measurement. This is a helper function for reporting observations.

GetCurrentLevel()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetCurrentLevel ( ) const

virtual

Get the current fitting level. This is a helper function for reporting observations.

GetElapsedIterations()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetElapsedIterations ( ) const

virtual

Get the number of elapsed iterations. This is a helper function for reporting observations.

GetLogBiasFieldControlPointLattice()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual const BiasFieldControlPointLatticeType* itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetLogBiasFieldControlPointLattice ( ) const

virtual

Typically, a reduced size image is used as input to the N4 filter using something like itkShrinkImageFilter. Since the output is a corrected version of the input, the user will probably want to apply the bias field correction to the full resolution image. This can be done by using the LogBiasFieldControlPointLattice to reconstruct the bias field at the full image resolution (using the class BSplineControlPointImageFilter).

GetMaskImage()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual const MaskImageType* itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetMaskImage ( ) const

virtual

Get mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

GetMaskLabel()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual MaskPixelType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetMaskLabel ( ) const

virtual

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

GetMaximumNumberOfIterations()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual VariableSizeArrayType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetMaximumNumberOfIterations ( ) const

virtual

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

GetNameOfClass()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual const char* itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetNameOfClass ( ) const

virtual

Runtime information support.

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

GetNumberOfControlPoints()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual ArrayType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetNumberOfControlPoints ( ) const

virtual

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.

GetNumberOfFittingLevels()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual ArrayType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetNumberOfFittingLevels ( ) const

virtual

Get the number of fitting levels. One of the contributions of N4 is the introduction of a multi-scale approach to fitting. This allows one to specify a B-spline mesh size for initial fitting followed by a doubling of the mesh resolution for each subsequent fitting level. Default = 1 level.

GetNumberOfHistogramBins()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetNumberOfHistogramBins ( ) const

virtual

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

GetSplineOrder()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetSplineOrder ( ) const

virtual

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

GetUseMaskLabel()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual bool itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetUseMaskLabel ( ) const

virtual

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

GetWienerFilterNoise()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::GetWienerFilterNoise ( ) const

virtual

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

New()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

static Pointer itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::New ( )

static

Standard New method.

PrintSelf()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::PrintSelf ( std::ostream &  os, Indent  indent  ) const

overrideprotectedvirtual

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

ReconstructBiasField()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

RealImagePointer itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::ReconstructBiasField

(

const BiasFieldControlPointLatticeType *

)

Reconstruct bias field given the control point lattice.

SetBiasFieldFullWidthAtHalfMaximum()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetBiasFieldFullWidthAtHalfMaximum ( RealType  _arg )

virtual

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

SetConfidenceImage()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetConfidenceImage ( const RealImageType *  input )

virtual

Set confidence image function. If a confidence image is specified, estimation of the bias field weights the contribution of each voxel according the value of the corresponding voxel in the confidence image. For example, when estimating the bias field using brain , one can use a soft segmentation of the white matter as the confidence image instead of using a hard segmentation of the white matter as the mask image (as has been done in the literature) as an alternative strategy to estimating the bias field.

Referenced by itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetInput3().

SetConvergenceThreshold()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetConvergenceThreshold ( RealType  _arg )

virtual

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.

SetInput1()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetInput1 ( const InputImageType *  image )

inline

The image expected for input for bias correction.

Definition at line 147 of file itkN4BiasFieldCorrectionImageFilter.h.

References itk::ImageToImageFilter< TInputImage, TOutputImage >::SetInput().

SetInput2()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetInput2 ( const MaskImageType *  mask )

inline

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 159 of file itkN4BiasFieldCorrectionImageFilter.h.

References itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetMaskImage().

SetInput3()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetInput3 ( const RealImageType *  image )

inline

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 204 of file itkN4BiasFieldCorrectionImageFilter.h.

References itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetConfidenceImage().

SetMaskImage()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetMaskImage ( const MaskImageType *  input )

virtual

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Referenced by itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetInput2().

SetMaskLabel()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetMaskLabel ( MaskPixelType  _arg )

virtual

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.

SetMaximumNumberOfIterations()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetMaximumNumberOfIterations ( VariableSizeArrayType  _arg )

virtual

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

SetNumberOfControlPoints()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetNumberOfControlPoints ( ArrayType  _arg )

virtual

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.

SetNumberOfFittingLevels() [1/2]

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetNumberOfFittingLevels ( ArrayType  _arg )

virtual

Set the number of fitting levels. One of the contributions of N4 is the introduction of a multi-scale approach to fitting. This allows one to specify a B-spline mesh size for initial fitting followed by a doubling of the mesh resolution for each subsequent fitting level. Default = 1 level.

Referenced by itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetNumberOfFittingLevels().

SetNumberOfFittingLevels() [2/2]

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetNumberOfFittingLevels ( unsigned int  n )

inline

Set the number of fitting levels. One of the contributions of N4 is the introduction of a multi-scale approach to fitting. This allows one to specify a B-spline mesh size for initial fitting followed by a doubling of the mesh resolution for each subsequent fitting level. Default = 1 level.

Definition at line 306 of file itkN4BiasFieldCorrectionImageFilter.h.

References itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetNumberOfFittingLevels().

SetNumberOfHistogramBins()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetNumberOfHistogramBins ( unsigned int  _arg )

virtual

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

SetSplineOrder()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetSplineOrder ( unsigned int  _arg )

virtual

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

SetUseMaskLabel()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetUseMaskLabel ( bool  _arg )

virtual

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

SetWienerFilterNoise()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SetWienerFilterNoise ( RealType  _arg )

virtual

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

SharpenImage()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::SharpenImage ( const RealImageType *  unsharpenedImage, RealImageType *  sharpenedImage  ) const

private

Sharpen the intensity histogram of the current estimate of the corrected image and map those results to a new estimate of the unsmoothed corrected image.

UpdateBiasFieldEstimate()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

RealImagePointer itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::UpdateBiasFieldEstimate ( RealImageType *  , std::vcl_size_t    )

private

Given the unsmoothed estimate of the bias field, this function smooths the estimate and adds the resulting control point values to the total bias field estimate.

UseMaskLabelOff()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::UseMaskLabelOff ( )

virtual

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

UseMaskLabelOn()

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

virtual void itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::UseMaskLabelOn ( )

virtual

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Member Data Documentation

ImageDimension

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

constexpr unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::ImageDimension = TInputImage::ImageDimension

staticconstexpr

ImageDimension constants

Definition at line 114 of file itkN4BiasFieldCorrectionImageFilter.h.

m_BiasFieldFullWidthAtHalfMaximum

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_BiasFieldFullWidthAtHalfMaximum { static_cast<RealType>(0.15) }

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 435 of file itkN4BiasFieldCorrectionImageFilter.h.

m_ConvergenceThreshold

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_ConvergenceThreshold { static_cast<RealType>(0.001) }

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 441 of file itkN4BiasFieldCorrectionImageFilter.h.

m_CurrentConvergenceMeasurement

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_CurrentConvergenceMeasurement

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 442 of file itkN4BiasFieldCorrectionImageFilter.h.

m_CurrentLevel

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_CurrentLevel { 0 }

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 443 of file itkN4BiasFieldCorrectionImageFilter.h.

m_ElapsedIterations

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_ElapsedIterations { 0 }

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 440 of file itkN4BiasFieldCorrectionImageFilter.h.

m_LogBiasFieldControlPointLattice

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

BiasFieldControlPointLatticeType::Pointer itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_LogBiasFieldControlPointLattice

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 447 of file itkN4BiasFieldCorrectionImageFilter.h.

m_MaskLabel

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

MaskPixelType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_MaskLabel

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 428 of file itkN4BiasFieldCorrectionImageFilter.h.

m_MaximumNumberOfIterations

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

VariableSizeArrayType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_MaximumNumberOfIterations

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 439 of file itkN4BiasFieldCorrectionImageFilter.h.

m_NumberOfControlPoints

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

ArrayType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_NumberOfControlPoints

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 450 of file itkN4BiasFieldCorrectionImageFilter.h.

m_NumberOfFittingLevels

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

ArrayType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_NumberOfFittingLevels

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 451 of file itkN4BiasFieldCorrectionImageFilter.h.

m_NumberOfHistogramBins

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_NumberOfHistogramBins { 200 }

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 433 of file itkN4BiasFieldCorrectionImageFilter.h.

m_SplineOrder

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

unsigned int itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_SplineOrder { 3 }

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 449 of file itkN4BiasFieldCorrectionImageFilter.h.

m_UseMaskLabel

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

bool itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_UseMaskLabel { false }

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 429 of file itkN4BiasFieldCorrectionImageFilter.h.

m_WienerFilterNoise

template<typename TInputImage , typename TMaskImage = Image<unsigned char, TInputImage::ImageDimension>, class TOutputImage = TInputImage>

RealType itk::N4BiasFieldCorrectionImageFilter< TInputImage, TMaskImage, TOutputImage >::m_WienerFilterNoise { static_cast<RealType>(0.01) }

private

Set mask image function. If a binary mask image is specified, only those input image voxels inside the mask image values are used in estimating the bias field.

Definition at line 434 of file itkN4BiasFieldCorrectionImageFilter.h.

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The documentation for this class was generated from the following file:

• itkN4BiasFieldCorrectionImageFilter.h