SimpleITK  1.3.0.dev208
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itk::simple::MultiLabelSTAPLEImageFilter Class Reference

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

typedef UnsignedIntegerPixelIDTypeList PixelIDTypeList
 
typedef MultiLabelSTAPLEImageFilter Self
 
- Public Types inherited from itk::simple::ImageFilter< 3 >
typedef ImageFilter Self
 
- Public Types inherited from itk::simple::ProcessObject
typedef ProcessObject Self
 

Public Member Functions

Image Execute (const std::vector< Image > &images)
 
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, uint64_t labelForUndecidedPixels, float terminationUpdateThreshold, unsigned int maximumNumberOfIterations, std::vector< float > priorProbabilities)
 
Image Execute (const Image &image1, uint64_t labelForUndecidedPixels, float terminationUpdateThreshold, unsigned int maximumNumberOfIterations, std::vector< float > priorProbabilities)
 
Image Execute (const Image &image1, const Image &image2, uint64_t labelForUndecidedPixels, float terminationUpdateThreshold, unsigned int maximumNumberOfIterations, std::vector< float > priorProbabilities)
 
Image Execute (const Image &image1, const Image &image2, const Image &image3, uint64_t labelForUndecidedPixels, float terminationUpdateThreshold, unsigned int maximumNumberOfIterations, std::vector< float > priorProbabilities)
 
Image Execute (const Image &image1, const Image &image2, const Image &image3, const Image &image4, uint64_t labelForUndecidedPixels, float terminationUpdateThreshold, unsigned int maximumNumberOfIterations, std::vector< float > priorProbabilities)
 
Image Execute (const Image &image1, const Image &image2, const Image &image3, const Image &image4, const Image &image5, uint64_t labelForUndecidedPixels, float terminationUpdateThreshold, unsigned int maximumNumberOfIterations, std::vector< float > priorProbabilities)
 
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 ()
 
SelfSetLabelForUndecidedPixels (uint64_t LabelForUndecidedPixels)
 
SelfSetMaximumNumberOfIterations (unsigned int MaximumNumberOfIterations)
 
SelfSetPriorProbabilities (std::vector< float > PriorProbabilities)
 
SelfSetTerminationUpdateThreshold (float TerminationUpdateThreshold)
 
std::string ToString () const
 
virtual ~MultiLabelSTAPLEImageFilter ()
 
- Public Member Functions inherited from itk::simple::ImageFilter< 3 >
 ImageFilter ()
 
virtual ~ImageFilter ()=0
 
- Public Member Functions inherited from itk::simple::ProcessObject
virtual void Abort ()
 
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
 

Private Types

typedef Image(Self::* MemberFunctionType) (const std::vector< Image > &)
 

Private Member Functions

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

Private Attributes

itk::ProcessObjectm_Filter
 
uint64_t m_LabelForUndecidedPixels
 
unsigned int m_MaximumNumberOfIterations
 
nsstd::auto_ptr< detail::MemberFunctionFactory< MemberFunctionType > > m_MemberFactory
 
nsstd::function< std::vector< float >unsigned int)> m_pfGetConfusionMatrix
 
std::vector< float > m_PriorProbabilities
 
float m_TerminationUpdateThreshold
 

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 void SetGlobalDefaultNumberOfThreads (unsigned int n)
 
static unsigned int GetGlobalDefaultNumberOfThreads ()
 
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...
 
- Protected Member Functions inherited from itk::simple::ProcessObject
virtual unsigned long AddITKObserver (const itk::EventObject &, itk::Command *)
 
virtual itk::ProcessObjectGetActiveProcess ()
 
virtual void OnActiveProcessDelete ()
 
virtual void onCommandDelete (const itk::simple::Command *cmd) SITK_NOEXCEPT
 
virtual void PreUpdate (itk::ProcessObject *p)
 
virtual void RemoveITKObserver (EventCommand &e)
 
- Protected Member Functions inherited from itk::simple::NonCopyable
 NonCopyable ()
 
- Static Protected Member Functions inherited from itk::simple::ImageFilter< 3 >
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 TImageType >
static Image CastITKToImage (TImageType *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)
 
static const itk::EventObjectGetITKEventObject (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 probaility 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 76 of file sitkMultiLabelSTAPLEImageFilter.h.

Member Typedef Documentation

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

Setup for member function dispatching

Definition at line 181 of file sitkMultiLabelSTAPLEImageFilter.h.

Define the pixels types supported by this filter

Definition at line 91 of file sitkMultiLabelSTAPLEImageFilter.h.

Definition at line 80 of file sitkMultiLabelSTAPLEImageFilter.h.

Constructor & Destructor Documentation

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

Destructor

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

Default Constructor that takes no arguments and initializes default parameters

Member Function Documentation

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

Execute the filter on the input images

Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
const Image image2 
)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
const Image image2,
const Image image3 
)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
const Image image2,
const Image image3,
const Image image4 
)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
const Image image2,
const Image image3,
const Image image4,
const Image image5 
)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const std::vector< Image > &  images,
uint64_t  labelForUndecidedPixels,
float  terminationUpdateThreshold,
unsigned int  maximumNumberOfIterations,
std::vector< float >  priorProbabilities 
)

Execute the filter on the input images with the given parameters

Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
uint64_t  labelForUndecidedPixels,
float  terminationUpdateThreshold,
unsigned int  maximumNumberOfIterations,
std::vector< float >  priorProbabilities 
)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
const Image image2,
uint64_t  labelForUndecidedPixels,
float  terminationUpdateThreshold,
unsigned int  maximumNumberOfIterations,
std::vector< float >  priorProbabilities 
)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
const Image image2,
const Image image3,
uint64_t  labelForUndecidedPixels,
float  terminationUpdateThreshold,
unsigned int  maximumNumberOfIterations,
std::vector< float >  priorProbabilities 
)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
const Image image2,
const Image image3,
const Image image4,
uint64_t  labelForUndecidedPixels,
float  terminationUpdateThreshold,
unsigned int  maximumNumberOfIterations,
std::vector< float >  priorProbabilities 
)
Image itk::simple::MultiLabelSTAPLEImageFilter::Execute ( const Image image1,
const Image image2,
const Image image3,
const Image image4,
const Image image5,
uint64_t  labelForUndecidedPixels,
float  terminationUpdateThreshold,
unsigned int  maximumNumberOfIterations,
std::vector< float >  priorProbabilities 
)
template<class TImageType >
Image itk::simple::MultiLabelSTAPLEImageFilter::ExecuteInternal ( const std::vector< Image > &  images)
private
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 148 of file sitkMultiLabelSTAPLEImageFilter.h.

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 106 of file sitkMultiLabelSTAPLEImageFilter.h.

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

Set maximum number of iterations.

Definition at line 126 of file sitkMultiLabelSTAPLEImageFilter.h.

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

Name of this class

Implements itk::simple::ProcessObject.

Definition at line 151 of file sitkMultiLabelSTAPLEImageFilter.h.

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 140 of file sitkMultiLabelSTAPLEImageFilter.h.

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

Set termination threshold based on confusion matrix parameter updates.

Definition at line 116 of file sitkMultiLabelSTAPLEImageFilter.h.

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

Set label value for undecided pixels.

Definition at line 99 of file sitkMultiLabelSTAPLEImageFilter.h.

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

Set maximum number of iterations.

Definition at line 121 of file sitkMultiLabelSTAPLEImageFilter.h.

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 133 of file sitkMultiLabelSTAPLEImageFilter.h.

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

Set termination threshold based on confusion matrix parameter updates.

Definition at line 111 of file sitkMultiLabelSTAPLEImageFilter.h.

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

Print ourselves out

Reimplemented from itk::simple::ProcessObject.

Friends And Related Function Documentation

Definition at line 186 of file sitkMultiLabelSTAPLEImageFilter.h.

Member Data Documentation

itk::ProcessObject* itk::simple::MultiLabelSTAPLEImageFilter::m_Filter
private

Definition at line 199 of file sitkMultiLabelSTAPLEImageFilter.h.

uint64_t itk::simple::MultiLabelSTAPLEImageFilter::m_LabelForUndecidedPixels
private

Definition at line 191 of file sitkMultiLabelSTAPLEImageFilter.h.

unsigned int itk::simple::MultiLabelSTAPLEImageFilter::m_MaximumNumberOfIterations
private

Definition at line 193 of file sitkMultiLabelSTAPLEImageFilter.h.

nsstd::auto_ptr<detail::MemberFunctionFactory<MemberFunctionType> > itk::simple::MultiLabelSTAPLEImageFilter::m_MemberFactory
private

Definition at line 188 of file sitkMultiLabelSTAPLEImageFilter.h.

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

Definition at line 196 of file sitkMultiLabelSTAPLEImageFilter.h.

std::vector<float> itk::simple::MultiLabelSTAPLEImageFilter::m_PriorProbabilities
private

Definition at line 194 of file sitkMultiLabelSTAPLEImageFilter.h.

float itk::simple::MultiLabelSTAPLEImageFilter::m_TerminationUpdateThreshold
private

Definition at line 192 of file sitkMultiLabelSTAPLEImageFilter.h.


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