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...

#include <sitkMultiLabelSTAPLEImageFilter.h>

Inheritance diagram for itk::simple::MultiLabelSTAPLEImageFilter:

Collaboration diagram for itk::simple::MultiLabelSTAPLEImageFilter:

Public Types
using	PixelIDTypeList = UnsignedIntegerPixelIDTypeList

using	Self = MultiLabelSTAPLEImageFilter

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 &image1)

Image	Execute (const Image &image1, const Image &image2)

Image	Execute (const Image &image1, const Image &image2, const Image &image3)

Image	Execute (const Image &image1, const Image &image2, const Image &image3, const Image &image4)

Image	Execute (const Image &image1, const Image &image2, const Image &image3, const Image &image4, const Image &image5)

Image	Execute (const std::vector< Image > &images)

std::vector< float >	GetConfusionMatrix (unsigned int input) const

uint64_t	GetLabelForUndecidedPixels () const

unsigned int	GetMaximumNumberOfIterations () const

std::string	GetName () const

std::vector< float >	GetPriorProbabilities () const

float	GetTerminationUpdateThreshold () const

	MultiLabelSTAPLEImageFilter ()

Self &	SetLabelForUndecidedPixels (uint64_t LabelForUndecidedPixels)

Self &	SetMaximumNumberOfIterations (unsigned int MaximumNumberOfIterations)

Self &	SetPriorProbabilities (std::vector< float > PriorProbabilities)

Self &	SetTerminationUpdateThreshold (float TerminationUpdateThreshold)

std::string	ToString () const

virtual	~MultiLabelSTAPLEImageFilter ()

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 std::vector< Image > &)

Private Member Functions
template<class TImageType >
Image	ExecuteInternal (const std::vector< Image > &images)

Private Attributes
itk::ProcessObject *	m_Filter {nullptr}

uint64_t	m_LabelForUndecidedPixels {std::numeric_limits<uint64_t>::max()}

unsigned int	m_MaximumNumberOfIterations {std::numeric_limits<unsigned int>::max()}

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

std::function< std::vector< float >unsigned int)>	m_pfGetConfusionMatrix

std::vector< float >	m_PriorProbabilities {std::vector<float>()}

float	m_TerminationUpdateThreshold {1e-5f}

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<unsigned int VImageDimension, unsigned int VLength, template< unsigned int > class TVector>
static Image	CastITKToImage (itk::Image< TVector< 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

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).

The labelings in the images are weighted relative to each other based on their "performance" as estimated by an expectation-maximization algorithm. In the process, a ground truth segmentation is estimated, and the estimated performances of the individual segmentations are relative to this estimated ground truth.

The algorithm is based on the binary STAPLE algorithm by Warfield et al. as published originally in

S. Warfield, K. Zou, W. Wells, "Validation of image segmentation and expert quality with an expectation-maximization algorithm" in MICCAI 2002: Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer-Verlag, Heidelberg, Germany, 2002, pp. 298-306

The multi-label algorithm implemented here is described in detail in

T. Rohlfing, D. B. Russakoff, and C. R. Maurer, Jr., "Performance-based classifier combination in atlas-based image segmentation using expectation-maximization parameter estimation," IEEE Transactions on Medical Imaging, vol. 23, pp. 983-994, Aug. 2004.

INPUTS: All input volumes to this filter must be segmentations of an image, that is, they must have discrete pixel values where each value represents a different segmented object.

Input volumes must all contain the same size RequestedRegions. Not all input images must contain all possible labels, but all label values must have the same meaning in all images.

The filter can optionally be provided with estimates for the a priori class probabilities through the SetPriorProbabilities function. If no estimate is provided, one is automatically generated by analyzing the relative frequencies of the labels in the input images.

OUTPUTS: The filter produces a single output volume. Each output pixel contains the label that has the highest probability of being the correct label, based on the performance models of the individual segmentations. If the maximum probability is not unique, i.e., if more than one label have a maximum probability, then an "undecided" label is assigned to that output pixel.

By default, the label used for undecided pixels is the maximum label value used in the input images plus one. Since it is possible for an image with 8 bit pixel values to use all 256 possible label values, it is permissible to combine 8 bit (i.e., byte) images into a 16 bit (i.e., short) output image.

In addition to the combined image, the estimated confusion matrices for each of the input segmentations can be obtained through the GetConfusionMatrix member function.

PARAMETERS: The label used for "undecided" labels can be set using SetLabelForUndecidedPixels. This functionality can be unset by calling UnsetLabelForUndecidedPixels.

A termination threshold for the EM iteration can be defined by calling SetTerminationUpdateThreshold. The iteration terminates once no single parameter of any confusion matrix changes by less than this threshold. Alternatively, a maximum number of iterations can be specified by calling SetMaximumNumberOfIterations. The algorithm may still terminate after a smaller number of iterations if the termination threshold criterion is satisfied.

EVENTS: This filter invokes IterationEvent() at each iteration of the E-M algorithm. Setting the AbortGenerateData() flag will cause the algorithm to halt after the current iteration and produce results just as if it had converged. The algorithm makes no attempt to report its progress since the number of iterations needed cannot be known in advance.

Author: Torsten Rohlfing, SRI International, Neuroscience Program

See also: itk::simple::MultiLabelSTAPLE for the procedural interface

Definition at line 81 of file sitkMultiLabelSTAPLEImageFilter.h.

Member Typedef Documentation

◆ MemberFunctionType

using itk::simple::MultiLabelSTAPLEImageFilter::MemberFunctionType = Image (Self::*)( const std::vector<Image> & )

private

Setup for member function dispatching

Definition at line 177 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ PixelIDTypeList

using itk::simple::MultiLabelSTAPLEImageFilter::PixelIDTypeList = UnsignedIntegerPixelIDTypeList

Define the pixels types supported by this filter

Definition at line 96 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ Self

using itk::simple::MultiLabelSTAPLEImageFilter::Self = MultiLabelSTAPLEImageFilter

Definition at line 85 of file sitkMultiLabelSTAPLEImageFilter.h.

Constructor & Destructor Documentation

◆ ~MultiLabelSTAPLEImageFilter()

virtual itk::simple::MultiLabelSTAPLEImageFilter::~MultiLabelSTAPLEImageFilter ( )

virtual

Destructor

◆ MultiLabelSTAPLEImageFilter()

itk::simple::MultiLabelSTAPLEImageFilter::MultiLabelSTAPLEImageFilter ( )

Default Constructor that takes no arguments and initializes default parameters

Member Function Documentation

◆ Execute() [1/6]

Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image & image1 )

◆ Execute() [2/6]

Image itk::simple::MultiLabelSTAPLEImageFilter::Execute	(	const Image &	image1,
		const Image &	image2
	)

◆ Execute() [3/6]

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

◆ Execute() [4/6]

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

◆ Execute() [5/6]

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

◆ Execute() [6/6]

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

Execute the filter on the input images

◆ ExecuteInternal()

template<class TImageType >

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

private

◆ GetConfusionMatrix()

std::vector<float> itk::simple::MultiLabelSTAPLEImageFilter::GetConfusionMatrix ( unsigned int input ) const

inline

Get confusion matrix for the i-th input segmentation.

This is an active measurement. It may be accessed while the filter is being executing in command call-backs and can be accessed after execution.

Definition at line 153 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ GetLabelForUndecidedPixels()

uint64_t itk::simple::MultiLabelSTAPLEImageFilter::GetLabelForUndecidedPixels ( ) const

inline

     Get label value used for undecided pixels.

After updating the filter, this function returns the actual label value used for undecided pixels in the current output. Note that this value is overwritten when SetLabelForUndecidedPixels is called and the new value only becomes effective upon the next filter update.

Definition at line 111 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ GetMaximumNumberOfIterations()

unsigned int itk::simple::MultiLabelSTAPLEImageFilter::GetMaximumNumberOfIterations ( ) const

inline

Set maximum number of iterations.

Definition at line 131 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ GetName()

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

inlinevirtual

Name of this class

Implements itk::simple::ProcessObject.

Definition at line 157 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ GetPriorProbabilities()

std::vector<float> itk::simple::MultiLabelSTAPLEImageFilter::GetPriorProbabilities ( ) const

inline

     Get prior class probabilities.

After updating the filter, this function returns the actual prior class probabilities. If these were not previously set by a call to SetPriorProbabilities, then they are estimated from the input segmentations and the result is available through this function.

Definition at line 145 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ GetTerminationUpdateThreshold()

float itk::simple::MultiLabelSTAPLEImageFilter::GetTerminationUpdateThreshold ( ) const

inline

Set termination threshold based on confusion matrix parameter updates.

Definition at line 121 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ SetLabelForUndecidedPixels()

Self& itk::simple::MultiLabelSTAPLEImageFilter::SetLabelForUndecidedPixels ( uint64_t LabelForUndecidedPixels )

inline

Set label value for undecided pixels.

Definition at line 104 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ SetMaximumNumberOfIterations()

Self& itk::simple::MultiLabelSTAPLEImageFilter::SetMaximumNumberOfIterations ( unsigned int MaximumNumberOfIterations )

inline

Set maximum number of iterations.

Definition at line 126 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ SetPriorProbabilities()

Self& itk::simple::MultiLabelSTAPLEImageFilter::SetPriorProbabilities ( std::vector< float > PriorProbabilities )

inline

     Set manual estimates for the a priori class probabilities. The size of the array must be greater than the value of the

largest label. The index into the array corresponds to the label value in the segmented image for the class.

Definition at line 138 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ SetTerminationUpdateThreshold()

Self& itk::simple::MultiLabelSTAPLEImageFilter::SetTerminationUpdateThreshold ( float TerminationUpdateThreshold )

inline

Set termination threshold based on confusion matrix parameter updates.

Definition at line 116 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ ToString()

std::string itk::simple::MultiLabelSTAPLEImageFilter::ToString ( ) const

virtual

Print ourselves out

Reimplemented from itk::simple::ProcessObject.

Friends And Related Function Documentation

◆ detail::MemberFunctionAddressor< MemberFunctionType >

friend struct detail::MemberFunctionAddressor< MemberFunctionType >

friend

Definition at line 182 of file sitkMultiLabelSTAPLEImageFilter.h.

Member Data Documentation

◆ m_Filter

itk::ProcessObject* itk::simple::MultiLabelSTAPLEImageFilter::m_Filter {nullptr}

private

Definition at line 199 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ m_LabelForUndecidedPixels

uint64_t itk::simple::MultiLabelSTAPLEImageFilter::m_LabelForUndecidedPixels {std::numeric_limits<uint64_t>::max()}

private

Definition at line 187 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ m_MaximumNumberOfIterations

unsigned int itk::simple::MultiLabelSTAPLEImageFilter::m_MaximumNumberOfIterations {std::numeric_limits<unsigned int>::max()}

private

Definition at line 191 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ m_MemberFactory

std::unique_ptr<detail::MemberFunctionFactory<MemberFunctionType> > itk::simple::MultiLabelSTAPLEImageFilter::m_MemberFactory

private

Definition at line 184 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ m_pfGetConfusionMatrix

std::function<std::vector<float>unsigned int)> itk::simple::MultiLabelSTAPLEImageFilter::m_pfGetConfusionMatrix

private

Definition at line 196 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ m_PriorProbabilities

std::vector<float> itk::simple::MultiLabelSTAPLEImageFilter::m_PriorProbabilities {std::vector<float>()}

private

Definition at line 193 of file sitkMultiLabelSTAPLEImageFilter.h.

◆ m_TerminationUpdateThreshold

float itk::simple::MultiLabelSTAPLEImageFilter::m_TerminationUpdateThreshold {1e-5f}

private

Definition at line 189 of file sitkMultiLabelSTAPLEImageFilter.h.

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

sitkMultiLabelSTAPLEImageFilter.h

Public Types

Public Member Functions

Private Types

Private Member Functions

Private Attributes

Friends

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ MemberFunctionType

◆ PixelIDTypeList

◆ Self

Constructor & Destructor Documentation

◆ ~MultiLabelSTAPLEImageFilter()

◆ MultiLabelSTAPLEImageFilter()

Member Function Documentation

◆ Execute() [1/6]

◆ Execute() [2/6]

◆ Execute() [3/6]

◆ Execute() [4/6]

◆ Execute() [5/6]

◆ Execute() [6/6]

◆ ExecuteInternal()

◆ GetConfusionMatrix()

◆ GetLabelForUndecidedPixels()

◆ GetMaximumNumberOfIterations()

◆ GetName()

◆ GetPriorProbabilities()

◆ GetTerminationUpdateThreshold()

◆ SetLabelForUndecidedPixels()

◆ SetMaximumNumberOfIterations()

◆ SetPriorProbabilities()

◆ SetTerminationUpdateThreshold()

◆ ToString()

Friends And Related Function Documentation

◆ detail::MemberFunctionAddressor< MemberFunctionType >

Member Data Documentation

◆ m_Filter

◆ m_LabelForUndecidedPixels

◆ m_MaximumNumberOfIterations

◆ m_MemberFactory

◆ m_pfGetConfusionMatrix

◆ m_PriorProbabilities

◆ m_TerminationUpdateThreshold