RCP-GS : Random Clustering Prior - Gibbs Sampler. More...

#include <iRCPGSAlgorithm.hh>

Inheritance diagram for iRCPGSAlgorithm:

Collaboration diagram for iRCPGSAlgorithm:

Public Member Functions
	iRCPGSAlgorithm ()

	~iRCPGSAlgorithm ()

int	InitSpecificOptions (string a_specificOptions)

void	ShowHelpSpecific ()
	Show help for the child algorithm. More...

Public Member Functions inherited from vAlgorithm
	vAlgorithm ()
	vAlgorithm constructor. Initialize the member variables to their default values. More...

virtual	~vAlgorithm ()
	vAlgorithm destructor. More...

int	Run ()
	Just call either the RunCPU or the RunGPU function as asked for. More...

int	RunCPU ()
	Perform the iterative loop of the algorithm. Function designed to be executed on the CPU only. More...

void	SetSaveSensitivityHistoFlag (bool a_saveSensitivityHistoFlag)
	Set the flag that specifies if the sensitivity image in histogram mode has to be saved for each subset/iteration. More...

void	SetSaveSubsetImageFlag (bool a_saveImageAfterSubsets)
	Set the flag that specifies if the image has to be saved for each subset. More...

void	SetSaveDynamicBasisCoefficientImages (bool a_saveDynamicBasisCoefficients)
	Set the flag that specifies if the dynamic basis functions coefficients images have to be saved. More...

void	SetOptimizerManager (oOptimizerManager *ap_OptimizerManager)
	Set the Optimizer Manager Object. More...

void	SetImageDimensionsAndQuantification (oImageDimensionsAndQuantification *ap_ImageDimensionsAndQuantification)
	Set the Image Dimensions and Quantification Object. More...

void	SetImageSpace (oImageSpace *ap_ImageSpace)
	Set the Image Space Object. More...

void	SetProjectorManager (oProjectorManager *ap_ProjectorManager)
	Set the Projector Manager Object. More...

void	SetImageConvolverManager (oImageConvolverManager *ap_ImageConvolverManager)
	Set the Image Convolver Manager Object. More...

void	SetImageProcessingManager (oImageProcessingManager *ap_ImageProcessingManager)
	Set the Image Processing Manager Object. More...

void	SetDynamicModelManager (oDynamicModelManager *ap_DynamicModelManager)
	Set the Dynamic Model Manager Object. More...

void	SetDeformationManager (oDeformationManager *ap_DeformationManager)
	Set the Deformation Manager Object. More...

void	SetDataFile (vDataFile **a2p_DataFile)
	Set the list of DataFile. More...

void	SetGPUflag (bool a_flagGPU)
	Set the GPU flag. More...

void	SetVerbose (int a_verboseLevel)
	Set Verbosity. More...

void	SetNbBeds (int a_nbBeds)
	Set number of beds (bed positions) More...

void	SetPathInitImage (string a_pathToInitialImage)
	Set path to an initial image. More...

void	SetPathToAttenuationImage (string a_pathToAttenuationImage)
	This function is used to set the path to the attenuation image. More...

void	SetPathToSensitivityImage (string a_pathToSensitivityImage)
	Set path to the sensitivity image. More...

void	SetPathToMultiModalImage (vector< string > a_pathToMultiModalImage)
	Set path to multimodal images. More...

void	SetPathToMaskImage (string a_pathToMaskImage)
	Set path to a mask image. More...

int	SetNbIterationsAndSubsets (const string &a_nbIterationsSubsets)
	Set the number of iterations and subsets. More...

int	SetOutputIterations (const string &a_outputIterations)
	Set the selected output iterations. More...

Protected Member Functions
int	StepBeforeIterationLoop ()
	This function is called at the beginning of the RunCPU function. More...

int	StepAfterIterationLoop ()
	This function is called at the end of the RunCPU function. More...

int	StepBeforeSubsetLoop (int a_iteration)
	This function is called before starting the data subset loop. More...

int	StepAfterSubsetLoop (int a_iteration)
	This function is called after finishing the data subset loop. More...

int	StepPreProcessInsideSubsetLoop (int a_iteration, int a_subset)
	This function is called right after starting the data subset loop. More...

int	StepInnerLoopInsideSubsetLoop (int a_iteration, int a_subset, int a_bed)
	This function is called inside the subset loop. It contains the core operations of the algorithm and must be implemented by child classes. More...

int	StepPostProcessInsideSubsetLoop (int a_iteration, int a_subset)

int	StepImageOutput (int a_iteration, int a_subset=-1)
	This function deals with everything about saving output images from the reconstruction. More...

int	ReadConfigurationFile (const string &a_configurationFile)

Private Member Functions
int	SampleConditionalCompleteData (int a_iteration, int a_subset, int a_bed)
	Gibbs sampler : first conditional probability (backprojection) More...

int	SampleConditionalClustering (int a_iteration)
	Gibbs sampler : second conditional probability (ddCRP links) More...

int	SampleConditionalClusterIntensity ()
	Gibbs sampler : third conditional probability (cluster intensity) More...

int	UpdateVisitedVoxels ()
	Check for voxels which do not contribute to recorded observed data. More...

int	InitializeHelperVar ()
	Allocate and initialize temporary variables, after the main variables have been initialized Assumption : the initial image and the sensitivity image have already been initialized. More...

int	ProcessMultiModalInfo ()
	Check input multimodal images. More...

int	GenerateCurrentImage ()
	Generate the current image estimation from the current sample of partition/clustering and cluster intensities. More...

int	ComputeFellowVoxelsList (vector< INTNB > &a_fellow_voxels, int a_current_voxel)
	Fill the input list of fellow voxels for the current type of neighbourhood and the input voxel, for ddCRP. More...

int	ComputeSumsPerClusters (int a_iteration)
	Compute sums of voxel features for each cluster. More...

int	SaveIntermediaryData (int a_iteration)
	Save potentially useful by-product variables specific to this algorithm. More...

Private Attributes
int	m_ddCRP

int	m_backprojection

int	m_neighbourhood

HPFLTNB	m_gammaShape

HPFLTNB	m_gammaRate

HPFLTNB	m_ddcrpAlpha

INTNB	m_multiModalLag

HPFLTNB	m_ddcrpAlphaIncrement

HPFLTNB *	mp_multiModalNoiseSigma

HPFLTNB *	mp_multiModalParam

INTNB *	mp_voxelClusterMapping

HPFLTNB *	mp_clusterValues

HPFLTNB **	mp_clusterN

HPFLTNB *	mp_clusterSensitivity

HPFLTNB **	mpp_clusterMultiModal

INTNB *	mp_clusterCount

INTNB *	mp_nextLink

vector< INTNB > *	mpv_parentLinks

vector< INTNB >	mv_newClusters

INTNB *	mp_listVoxelIndices

INTNB **	mp_listEventsIndices

INTNB ****	m4p_EventsBackprojectionTrace

bool *	mp_listRelevantVoxelIndices

HPFLTNB *	temp_count_multimodal

HPFLTNB	m_ddcrpLogAlpha

HPFLTNB	m_currentMeanClusterVolume

HPFLTNB	m_meanClusterVolumeMin

HPFLTNB	m_meanClusterVolumeMax

FLTNB *	mp_permanentBackwardImage

Additional Inherited Members
Protected Attributes inherited from vAlgorithm
int	m_nbIterations

int *	mp_nbSubsets

bool *	mp_outputIterations

int	m_verbose

bool	m_flagGPU

oImageDimensionsAndQuantification *	mp_ID

vDataFile **	m2p_DataFile

oProjectorManager *	mp_ProjectorManager

oOptimizerManager *	mp_OptimizerManager

oDeformationManager *	mp_DeformationManager

oDynamicModelManager *	mp_DynamicModelManager

oImageSpace *	mp_ImageSpace

oImageConvolverManager *	mp_ImageConvolverManager

oImageProcessingManager *	mp_ImageProcessingManager

int	m_nbBeds

string	m_pathToInitialImg

string	m_pathToAtnImg

string	m_pathToSensitivityImg

vector< string >	m_pathToMultiModalImg

string	m_pathToMaskImg

bool	m_saveSensitivityHistoFlag

bool	m_saveImageAfterSubsets

bool	m_saveDynamicBasisCoefficients

Detailed Description

RCP-GS : Random Clustering Prior - Gibbs Sampler.

Sampling of the posterior probability distribution (Bayesian inference) Image prior : ddCRP, with intensity ~ Gamma (conjugate prior for Poisson likelihood) Multinomial distribution for the backprojection from acquired data into (latent) emissions from voxel j into projection i

Definition at line 42 of file iRCPGSAlgorithm.hh.

Constructor & Destructor Documentation

◆ iRCPGSAlgorithm()

iRCPGSAlgorithm::iRCPGSAlgorithm ( )

Definition at line 34 of file iRCPGSAlgorithm.cc.

◆ ~iRCPGSAlgorithm()

iRCPGSAlgorithm::~iRCPGSAlgorithm ( )

Definition at line 67 of file iRCPGSAlgorithm.cc.

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Member Function Documentation

◆ ComputeFellowVoxelsList()

int iRCPGSAlgorithm::ComputeFellowVoxelsList	(	vector< INTNB > &	a_fellow_voxels,
		int	a_current_voxel
	)

private

Fill the input list of fellow voxels for the current type of neighbourhood and the input voxel, for ddCRP.

Returns: 0 if success, positive value otherwise.

Definition at line 1790 of file iRCPGSAlgorithm.cc.

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◆ ComputeSumsPerClusters()

int iRCPGSAlgorithm::ComputeSumsPerClusters ( int a_iteration )

private

Compute sums of voxel features for each cluster.

Returns: 0 if success, positive value otherwise.

Definition at line 1356 of file iRCPGSAlgorithm.cc.

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◆ GenerateCurrentImage()

int iRCPGSAlgorithm::GenerateCurrentImage ( )

private

Generate the current image estimation from the current sample of partition/clustering and cluster intensities.

Returns: 0 if success, positive value otherwise.

Definition at line 1852 of file iRCPGSAlgorithm.cc.

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◆ InitializeHelperVar()

int iRCPGSAlgorithm::InitializeHelperVar ( )

private

Allocate and initialize temporary variables, after the main variables have been initialized Assumption : the initial image and the sensitivity image have already been initialized.

Returns: 0 if success, positive value otherwise.

Definition at line 543 of file iRCPGSAlgorithm.cc.

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◆ InitSpecificOptions()

int iRCPGSAlgorithm::InitSpecificOptions ( string a_specificOptions )

virtual

Parameters

a_specificOptions

Returns: 0

Reimplemented from vAlgorithm.

Definition at line 158 of file iRCPGSAlgorithm.cc.

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◆ ProcessMultiModalInfo()

int iRCPGSAlgorithm::ProcessMultiModalInfo ( )

private

Check input multimodal images.

Returns: 0 if success, positive value otherwise.

Definition at line 688 of file iRCPGSAlgorithm.cc.

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◆ ReadConfigurationFile()

int iRCPGSAlgorithm::ReadConfigurationFile ( const string & a_configurationFile )

protected

Definition at line 463 of file iRCPGSAlgorithm.cc.

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◆ SampleConditionalClustering()

int iRCPGSAlgorithm::SampleConditionalClustering ( int a_iteration )

private

Gibbs sampler : second conditional probability (ddCRP links)

Returns: 0 if success, positive value otherwise.

Definition at line 1441 of file iRCPGSAlgorithm.cc.

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◆ SampleConditionalClusterIntensity()

int iRCPGSAlgorithm::SampleConditionalClusterIntensity ( )

private

Gibbs sampler : third conditional probability (cluster intensity)

Returns: 0 if success, positive value otherwise.

Definition at line 1738 of file iRCPGSAlgorithm.cc.

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◆ SampleConditionalCompleteData()

int iRCPGSAlgorithm::SampleConditionalCompleteData	(	int	a_iteration,
		int	a_subset,
		int	a_bed
	)

private

Gibbs sampler : first conditional probability (backprojection)

Returns: 0 if success, positive value otherwise.

Definition at line 912 of file iRCPGSAlgorithm.cc.

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◆ SaveIntermediaryData()

private int iRCPGSAlgorithm::SaveIntermediaryData ( int a_iteration )

private

Save potentially useful by-product variables specific to this algorithm.

Returns: 0 if success, positive value otherwise.

◆ ShowHelpSpecific()

void iRCPGSAlgorithm::ShowHelpSpecific ( )

virtual

Show help for the child algorithm.

Reimplemented from vAlgorithm.

Definition at line 2031 of file iRCPGSAlgorithm.cc.

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◆ StepAfterIterationLoop()

int iRCPGSAlgorithm::StepAfterIterationLoop ( )

protectedvirtual

This function is called at the end of the RunCPU function.

Returns: 0 if success, positive value otherwise.

Reimplemented from vAlgorithm.

Definition at line 1879 of file iRCPGSAlgorithm.cc.

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◆ StepAfterSubsetLoop()

int iRCPGSAlgorithm::StepAfterSubsetLoop ( int a_iteration )

protectedvirtual

This function is called after finishing the data subset loop.

Parameters

a_iteration : iteration index

Returns: 0 if success, positive value otherwise.

Reimplemented from vAlgorithm.

Definition at line 1910 of file iRCPGSAlgorithm.cc.

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◆ StepBeforeIterationLoop()

int iRCPGSAlgorithm::StepBeforeIterationLoop ( )

protectedvirtual

This function is called at the beginning of the RunCPU function.

Returns: 0 if success, positive value otherwise.

Reimplemented from vAlgorithm.

Definition at line 715 of file iRCPGSAlgorithm.cc.

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◆ StepBeforeSubsetLoop()

int iRCPGSAlgorithm::StepBeforeSubsetLoop ( int a_iteration )

protectedvirtual

This function is called before starting the data subset loop.

Parameters

a_iteration : iteration index

Returns: 0 if success, positive value otherwise.

Reimplemented from vAlgorithm.

Definition at line 1899 of file iRCPGSAlgorithm.cc.

◆ StepImageOutput()

int iRCPGSAlgorithm::StepImageOutput	(	int	a_iteration,
		int	a_subset = `-1`
	)

protectedvirtual

This function deals with everything about saving output images from the reconstruction.

Implements vAlgorithm.

Definition at line 1938 of file iRCPGSAlgorithm.cc.

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◆ StepInnerLoopInsideSubsetLoop()

int iRCPGSAlgorithm::StepInnerLoopInsideSubsetLoop	(	int	a_iteration,
		int	a_subset,
		int	a_bed
	)

protectedvirtual

This function is called inside the subset loop.
It contains the core operations of the algorithm and must be implemented by child classes.

Parameters

a_iteration	: iteration index
a_subset	: subset index
a_bed	: bed position

Returns: 0 if success, positive value otherwise.

Implements vAlgorithm.

Definition at line 776 of file iRCPGSAlgorithm.cc.

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◆ StepPostProcessInsideSubsetLoop()

int iRCPGSAlgorithm::StepPostProcessInsideSubsetLoop	(	int	a_iteration,
		int	a_subset
	)

protectedvirtual

Reimplemented from vAlgorithm.

Definition at line 792 of file iRCPGSAlgorithm.cc.

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◆ StepPreProcessInsideSubsetLoop()

int iRCPGSAlgorithm::StepPreProcessInsideSubsetLoop	(	int	a_iteration,
		int	a_subset
	)

protectedvirtual

This function is called right after starting the data subset loop.

This function is called right after starting the subset loop.
.

Parameters

a_iteration	: iteration index
a_subset	: subset index

Returns: 0 if success, positive value otherwise.

Reimplemented from vAlgorithm.

Definition at line 760 of file iRCPGSAlgorithm.cc.

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◆ UpdateVisitedVoxels()

int iRCPGSAlgorithm::UpdateVisitedVoxels ( )

private

Check for voxels which do not contribute to recorded observed data.

Returns: 0 if success, positive value otherwise.

Definition at line 1420 of file iRCPGSAlgorithm.cc.

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Member Data Documentation

◆ m4p_EventsBackprojectionTrace

INTNB**** iRCPGSAlgorithm::m4p_EventsBackprojectionTrace

private

Trace of the backprojection destination for each observed count at previous iteration, Number of beds x Number of events x Number of TOF bins x Number of counts

Definition at line 158 of file iRCPGSAlgorithm.hh.

◆ m_backprojection

int iRCPGSAlgorithm::m_backprojection

private

flag describing the multinomial backprojection of the current iteration/subset data (sampling of conditional complete data): 0 = the previous backprojection state is cleared, as for ML-EM 1 = update of the previous backprojection state 2 = backprojection marginalized over cluster intensity, implies update of the previous backprojection state

Definition at line 133 of file iRCPGSAlgorithm.hh.

◆ m_currentMeanClusterVolume

HPFLTNB iRCPGSAlgorithm::m_currentMeanClusterVolume

private

helper variable for the average cluster volume after each iteration/subset

Definition at line 163 of file iRCPGSAlgorithm.hh.

◆ m_ddCRP

int iRCPGSAlgorithm::m_ddCRP

private

flag describing the ddCRP prior : 0 = no ddCRP, 1 = original ddCRP, 2 = modified ddCRP

Definition at line 132 of file iRCPGSAlgorithm.hh.

◆ m_ddcrpAlpha

HPFLTNB iRCPGSAlgorithm::m_ddcrpAlpha

private

ddCRP : the unnormalized probability of drawing a self link

Definition at line 140 of file iRCPGSAlgorithm.hh.

◆ m_ddcrpAlphaIncrement

HPFLTNB iRCPGSAlgorithm::m_ddcrpAlphaIncrement

private

Multiplicative increment for optimizing the ddCRP alpha parameter through iterations

Definition at line 142 of file iRCPGSAlgorithm.hh.

◆ m_ddcrpLogAlpha

HPFLTNB iRCPGSAlgorithm::m_ddcrpLogAlpha

private

helper variable for precomputed log of ddCRP : the probability of drawing a self link (not normalized)

Definition at line 162 of file iRCPGSAlgorithm.hh.

◆ m_gammaRate

HPFLTNB iRCPGSAlgorithm::m_gammaRate

private

Gamma prior distribution rate parameter

Definition at line 139 of file iRCPGSAlgorithm.hh.

◆ m_gammaShape

HPFLTNB iRCPGSAlgorithm::m_gammaShape

private

Gamma prior distribution shape parameter

Definition at line 138 of file iRCPGSAlgorithm.hh.

◆ m_meanClusterVolumeMax

HPFLTNB iRCPGSAlgorithm::m_meanClusterVolumeMax

private

Maximum threshold for average cluster volume (in mm3), used for adapting ddCRP alpha automatically through iterations

Definition at line 165 of file iRCPGSAlgorithm.hh.

◆ m_meanClusterVolumeMin

HPFLTNB iRCPGSAlgorithm::m_meanClusterVolumeMin

private

Minimum threshold for average cluster volume (in mm3), used for adapting ddCRP alpha automatically through iterations

Definition at line 164 of file iRCPGSAlgorithm.hh.

◆ m_multiModalLag

INTNB iRCPGSAlgorithm::m_multiModalLag

private

Number of iterations after which the multimodal images start affecting voxels clustering

Definition at line 141 of file iRCPGSAlgorithm.hh.

◆ m_neighbourhood

int iRCPGSAlgorithm::m_neighbourhood

private

Number of voxels in the neighbourhood

Definition at line 137 of file iRCPGSAlgorithm.hh.

◆ mp_clusterCount

INTNB* iRCPGSAlgorithm::mp_clusterCount

private

Number of voxels per cluster

Definition at line 152 of file iRCPGSAlgorithm.hh.

◆ mp_clusterN

HPFLTNB** iRCPGSAlgorithm::mp_clusterN

private

Ns : sum over cluster voxels and all LORs of latent backprojected variable (complete data), requires HPFLTNB precision, can be threaded

Definition at line 149 of file iRCPGSAlgorithm.hh.

◆ mp_clusterSensitivity

HPFLTNB* iRCPGSAlgorithm::mp_clusterSensitivity

private

Sensitivity : sum over cluster voxels and all LORs of system matrix components, requires HPFLTNB precision

Definition at line 150 of file iRCPGSAlgorithm.hh.

◆ mp_clusterValues

HPFLTNB* iRCPGSAlgorithm::mp_clusterValues

private

Values (here voxel intensities) associated with each cluster

Definition at line 148 of file iRCPGSAlgorithm.hh.

◆ mp_listEventsIndices

INTNB** iRCPGSAlgorithm::mp_listEventsIndices

private

List of events indices, per bed, used for random shuffling

Definition at line 157 of file iRCPGSAlgorithm.hh.

◆ mp_listRelevantVoxelIndices

bool* iRCPGSAlgorithm::mp_listRelevantVoxelIndices

private

Indices of voxels which will be taken into account in the algorithm; all the other voxels are regarded as background and set to 0

Definition at line 160 of file iRCPGSAlgorithm.hh.

◆ mp_listVoxelIndices

INTNB* iRCPGSAlgorithm::mp_listVoxelIndices

private

List of voxel indices, used for random shuffling

Definition at line 156 of file iRCPGSAlgorithm.hh.

◆ mp_multiModalNoiseSigma

HPFLTNB* iRCPGSAlgorithm::mp_multiModalNoiseSigma

private

Standard deviation of Gaussian noise in multimodal images

Definition at line 144 of file iRCPGSAlgorithm.hh.

◆ mp_multiModalParam

HPFLTNB* iRCPGSAlgorithm::mp_multiModalParam

private

Parameter for the standard deviation of the prior on multimodal images

Definition at line 145 of file iRCPGSAlgorithm.hh.

◆ mp_nextLink

INTNB* iRCPGSAlgorithm::mp_nextLink

private

Mapping : voxel index -> next voxel index (link from this voxel to another voxel)

Definition at line 153 of file iRCPGSAlgorithm.hh.

◆ mp_permanentBackwardImage

FLTNB* iRCPGSAlgorithm::mp_permanentBackwardImage

private

A buffer image used for holding the complete up-to-date backward image at any time. It is updated at each iteration/subset, and used in backprojection modes 1 and 2

Definition at line 166 of file iRCPGSAlgorithm.hh.

◆ mp_voxelClusterMapping

INTNB* iRCPGSAlgorithm::mp_voxelClusterMapping

private

Mapping : voxel index -> cluster index

Definition at line 147 of file iRCPGSAlgorithm.hh.

◆ mpp_clusterMultiModal

HPFLTNB** iRCPGSAlgorithm::mpp_clusterMultiModal

private

Multimodal image(s) : sum over cluster voxels, requires HPFLTNB precision

Definition at line 151 of file iRCPGSAlgorithm.hh.

◆ mpv_parentLinks

vector<INTNB>* iRCPGSAlgorithm::mpv_parentLinks

private

Mapping : voxel index -> list of previous voxels (links from other voxels to this voxel)

Definition at line 154 of file iRCPGSAlgorithm.hh.

◆ mv_newClusters

vector<INTNB> iRCPGSAlgorithm::mv_newClusters

private

Indices of free available (empty) clusters (the number of clusters <= the number of voxels + 1)

Definition at line 155 of file iRCPGSAlgorithm.hh.

◆ temp_count_multimodal

HPFLTNB* iRCPGSAlgorithm::temp_count_multimodal

private

helper variable for the second sampling step, just to avoid allocating repeatedly >

Definition at line 161 of file iRCPGSAlgorithm.hh.

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

Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ iRCPGSAlgorithm()

◆ ~iRCPGSAlgorithm()

Member Function Documentation

◆ ComputeFellowVoxelsList()

◆ ComputeSumsPerClusters()

◆ GenerateCurrentImage()

◆ InitializeHelperVar()

◆ InitSpecificOptions()

◆ ProcessMultiModalInfo()

◆ ReadConfigurationFile()

◆ SampleConditionalClustering()

◆ SampleConditionalClusterIntensity()

◆ SampleConditionalCompleteData()

◆ SaveIntermediaryData()

◆ ShowHelpSpecific()

◆ StepAfterIterationLoop()

◆ StepAfterSubsetLoop()

◆ StepBeforeIterationLoop()

◆ StepBeforeSubsetLoop()

◆ StepImageOutput()

◆ StepInnerLoopInsideSubsetLoop()

◆ StepPostProcessInsideSubsetLoop()

◆ StepPreProcessInsideSubsetLoop()

◆ UpdateVisitedVoxels()

Member Data Documentation

◆ m4p_EventsBackprojectionTrace

◆ m_backprojection

◆ m_currentMeanClusterVolume

◆ m_ddCRP

◆ m_ddcrpAlpha

◆ m_ddcrpAlphaIncrement

◆ m_ddcrpLogAlpha

◆ m_gammaRate

◆ m_gammaShape

◆ m_meanClusterVolumeMax

◆ m_meanClusterVolumeMin

◆ m_multiModalLag

◆ m_neighbourhood

◆ mp_clusterCount

◆ mp_clusterN

◆ mp_clusterSensitivity

◆ mp_clusterValues

◆ mp_listEventsIndices

◆ mp_listRelevantVoxelIndices

◆ mp_listVoxelIndices

◆ mp_multiModalNoiseSigma

◆ mp_multiModalParam

◆ mp_nextLink

◆ mp_permanentBackwardImage

◆ mp_voxelClusterMapping

◆ mpp_clusterMultiModal

◆ mpv_parentLinks

◆ mv_newClusters

◆ temp_count_multimodal