This class implements a 1 compartiment model, to model kinetics of radiotracers such as radiowater. More...

#include <i1TCModel.hh>

Inheritance diagram for i1TCModel:

Collaboration diagram for i1TCModel:

Public Member Functions
	i1TCModel ()
	Constructor of i1TCModel. Simply set all data members to default values. More...

	~i1TCModel ()
	Destructor of i1TCModel. More...

int	CheckSpecificParameters ()
	This function is used to check whether all member variables have been correctly initialized or not. More...

int	ReadAndCheckConfigurationFileSpecific ()
	This function is used to read options from a configuration file. More...

int	ReadAndCheckOptionsList (string a_listOptions)
	This function is used to read parameters from a string. More...

int	InitializeSpecific ()
	This function is used to initialize parametric images and basis functions. More...

void	ShowHelp ()
	Print out specific help about the implementation of the model model and its initialization. More...

int	EstimateModelParameters (oImageSpace *ap_Image, int a_ite, int a_sset)
	Estimate K1, k2, Va parametric images. More...

int	EstimateImageWithModel (oImageSpace *ap_Image, int a_ite, int a_sset)
	Estimate image using model parametric images and basis functions. More...

Public Member Functions inherited from vDynamicModel
	vDynamicModel ()
	Constructor of vDynamicModel. Simply set all data members to default values. More...

virtual	~vDynamicModel ()
	Destructor of vDynamicModel. More...

void	SetImageDimensionsAndQuantification (oImageDimensionsAndQuantification *ap_ImageDimensionsAndQuantification)
	Set the image dimensions in use. More...

void	SetVerbose (int a_verbose)
	Set the verbose level. More...

virtual int	CheckParameters ()
	This function is used to check parameters after the latter have been all set using Set functions. More...

int	ReadAndCheckConfigurationFile (string a_fileOptions)
	This function is used to read options from a configuration file. It looks for the parameters implemented by the mother class, such as 'No image update', 'No parameters update', or 'Save parametric images'. More...

int	Initialize ()
	A public function used to initialize the dynamic model. More...

virtual int	EstimateModel (oImageSpace *ap_Image, int a_ite, int a_sset)
	This function checks if the EstimateModelParameters() function (specific to each model) must be called at this stage of the reconstruction depending on the m_xxxUpdateflags. More...

virtual int	EstimateImage (oImageSpace *ap_Image, int a_ite, int a_sset)

int	SaveParametricImages (int a_iteration, int a_subset=-1)
	This function is virtual it can be overloaded by children if required. More...

virtual int	ApplyOutputFOVMaskingOnParametricImages ()
	Mask the outside of the transaxial FOV based on the m_fovOutPercent. More...

bool	GetAICflag ()

bool	GetModelBasisFunctionsRequiredFlag ()

int	GetNbTimeBasisFunctions ()

FLTNB **	GetTimeBasisFunctions ()

virtual void	ComputeOutputParImage ()
	Compute output image using the m2p_parametricImages matrix Store the result in the m2p_outputParImages matrix. More...

int	NNLS (FLTNB *A, int m, int n, FLTNB B, FLTNB X, FLTNB rnorm, FLTNB wp, FLTNB zzp, int *indexp)
	Implementation of NNLS (non-negative least squares) algorithm Derived from Turku PET center libraries (authors: Vesa Oikonen and Kaisa Sederholm) This routine is based on the text and fortran code in C.L. Lawson and R.J. Hanson, Solving Least Squares Problems, Prentice-Hall, Englewood Cliffs, New Jersey, 1974. More...

Protected Attributes
bool	m_savePImgFlag

int	m_OptimisationMethodFlag

FLTNB **	m2p_ct

FLTNB **	m2p_cti

FLTNB *	mp_w

FLTNB ***	m3p_nnlsA

FLTNB **	m2p_nnlsB

FLTNB **	m2p_nnlsMat

uint16_t	m_nnlsN =3

FLTNB *	mp_parUpperBounds

FLTNB *	mp_parLowerBounds

FLTNB	m_RRcst

bool	m_ridgeRegressionFlag

FLTNB *	mp_DT2

FLTNB *	mp_wpoQ

FLTNB *	mp_wpoA

FLTNB **	m2p_wpoP

FLTNB **	m2p_wpoFD

FLTNB **	m2p_wpoBD

bool	m_intMethodFlag

oMatrix **	mp_Y

oMatrix **	mp_X

oMatrix **	mp_Xt

oMatrix **	mp_XtX

oMatrix **	mp_LSnum

oMatrix **	mp_LSden

oMatrix **	mp_Theta

oMatrix *	mp_RRm

oMatrix *	mp_RRw

oMatrix **	mp_RRnum

FLTNB *	mp_VaImage

Protected Attributes inherited from vDynamicModel
oImageDimensionsAndQuantification *	mp_ID

int	m_verbose

int	m_nbTimeBF

int	m_nbWeightFactors

int	m_nbModelParam

int	m_nbRGModelParam

int	m_nbCGModelParam

string	m_AICfile

oArterialInputCurve *	mp_ArterialInputCurve

FLTNB **	m2p_parametricImages

FLTNB *	mp_blackListedvoxelsImage

FLTNB **	m2p_nestedModelTimeBasisFunctions

FLTNB **	m2p_outputParImages

FLTNB **	m2p_RGParametricImages

FLTNB **	m2p_CGParametricImages

string	m_fileOptions

string	m_listOptions

bool	m_checked

bool	m_initialized

bool	m_saveParImageFlag

bool	m_saveBlacklistedImageMaskFlag

bool	m_AICfileProvided

bool	m_ModelSpecificBasisFunctionsRequired

bool	m_noImageUpdateFlag

bool	m_noParametersUpdateFlag

int	m_startIteUpdateFlag

FLTNB *	mp_maskModel

INTNB	m_nbVoxelsMask

FLTNB *	mp_w

FLTNB ***	m3p_nnlsA

FLTNB **	m2p_nnlsB

FLTNB **	m2p_nnlsMat

FLTNB **	m2p_nnlsX

FLTNB **	m2p_nnlsWp

int **	m2p_nnlsIdx

uint16_t	m_nnlsN =0

Private Member Functions
int	EstimateModelParametersWithLS (oImageSpace *ap_ImageS)
	Estimate K1, k2, Va parametric images using LS. More...

int	EstimateModelParametersWithNNLS (oImageSpace *ap_ImageS)
	Estimate K1, k2, Va parametric images using NNLS. More...

int	EstimateModelParametersWithBF (oImageSpace *ap_ImageS)
	Estimate K1, k2, Va parametric images using basis functions approach. More...

int	RRLS (uint16_t a_nP, uint16_t a_nT, FLTNB *a2p_model, FLTNB ap_data, FLTNB ap_w, FLTNB ap_result)
	Non-linear least square estimator with Ridge-Regression. More...

int	LS (uint16_t a_nP, uint16_t a_nT, FLTNB *a2p_model, FLTNB ap_data, FLTNB ap_w, FLTNB ap_result)
	Non-linear least square estimator. More...

FLTNB	WPOinc (uint32_t a_time, FLTNB tac, FLTNB b_tac, FLTNB bb_tac, FLTNB n_tac)
	Estimate the next integration value for a specific time point of a tac using WPO. More...

int	IntegrateTAC (FLTNB ap_tac, FLTNB ap_citac, int a_th)
	Call one of the TAC integration method. More...

int	WPO (FLTNB ap_tac, FLTNB ap_citac, int a_th)
	return integral for each time point t (WPO_S), and cumulative integral (cumWPO_S ) More...

int	Trapz (FLTNB ap_tac, FLTNB ap_citac)
	return integral for each time point t (WPO_S), and cumulative integral (cumWPO_S ) More...

Detailed Description

This class implements a 1 compartiment model, to model kinetics of radiotracers such as radiowater.

Definition at line 73 of file i1TCModel.hh.

Constructor & Destructor Documentation

◆ i1TCModel()

i1TCModel::i1TCModel ( )

Constructor of i1TCModel. Simply set all data members to default values.

Definition at line 51 of file i1TCModel.cc.

◆ ~i1TCModel()

i1TCModel::~i1TCModel ( )

Destructor of i1TCModel.

Definition at line 110 of file i1TCModel.cc.

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Member Function Documentation

◆ CheckSpecificParameters()

int i1TCModel::CheckSpecificParameters ( )

virtual

This function is used to check whether all member variables have been correctly initialized or not.

Returns: 0 if success, positive value otherwise.

Implements vDynamicModel.

Definition at line 455 of file i1TCModel.cc.

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◆ EstimateImageWithModel()

int i1TCModel::EstimateImageWithModel	(	oImageSpace *	ap_Image,
		int	a_ite,
		int	a_sset
	)

virtual

Estimate image using model parametric images and basis functions.

Parameters

ap_ImageS	: pointer to the ImageSpace
a_ite	: index of the actual iteration (not used)
a_sset	: index of the actual subset (not used)

Returns: 0 if success, other value otherwise.

Implements vDynamicModel.

Definition at line 1737 of file i1TCModel.cc.

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◆ EstimateModelParameters()

int i1TCModel::EstimateModelParameters	(	oImageSpace *	ap_Image,
		int	a_ite,
		int	a_sset
	)

virtual

Estimate K1, k2, Va parametric images.

Parameters

ap_ImageS	: pointer to the ImageSpace
a_ite	: index of the actual iteration (not used)
a_sset	: index of the actual subset (not used)

Returns: 0 if success, other value otherwise.

Implements vDynamicModel.

Definition at line 898 of file i1TCModel.cc.

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◆ EstimateModelParametersWithBF()

int i1TCModel::EstimateModelParametersWithBF ( oImageSpace * ap_ImageS )

private

Estimate K1, k2, Va parametric images using basis functions approach.

Parameters

ap_ImageS : pointer to the ImageSpace

Returns: 0 if success, other value otherwise.

Definition at line 1181 of file i1TCModel.cc.

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◆ EstimateModelParametersWithLS()

int i1TCModel::EstimateModelParametersWithLS ( oImageSpace * ap_ImageS )

private

Estimate K1, k2, Va parametric images using LS.

Parameters

ap_ImageS : pointer to the ImageSpace

Returns: 0 if success, other value otherwise.

Definition at line 1216 of file i1TCModel.cc.

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◆ EstimateModelParametersWithNNLS()

int i1TCModel::EstimateModelParametersWithNNLS ( oImageSpace * ap_ImageS )

private

Estimate K1, k2, Va parametric images using NNLS.

Parameters

ap_ImageS : pointer to the ImageSpace

Returns: 0 if success, other value otherwise.

Definition at line 1002 of file i1TCModel.cc.

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◆ InitializeSpecific()

int i1TCModel::InitializeSpecific ( )

virtual

This function is used to initialize parametric images and basis functions.

Returns: 0 if success, other value otherwise.

Implements vDynamicModel.

Definition at line 518 of file i1TCModel.cc.

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◆ IntegrateTAC()

int i1TCModel::IntegrateTAC	(	FLTNB *	ap_tac,
		FLTNB *	ap_citac,
		int	a_th
	)

private

Call one of the TAC integration method.

Parameters

ap_tac	: vector with nb time frames elements containing the time activity curve from which integral will be computed
ap_citac	: (returned) vector with nb time frames elements recovering the cumulative integral for each time point t
a_th	: thread index

Returns: 0 if success, positive value otherwise

Definition at line 1898 of file i1TCModel.cc.

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◆ LS()

int i1TCModel::LS	(	uint16_t	a_nP,
		uint16_t	a_nT,
		FLTNB **	a2p_model,
		FLTNB *	ap_data,
		FLTNB *	ap_w,
		FLTNB *	ap_result
	)

private

Non-linear least square estimator.

Parameters

a_nP	: number of parameters (P)
a_nT	: number of data samples (T)
a2p_model	: matrix containing the model functions (TxP elts)
ap_data	: data vector (T elts)
ap_w	: vector containing the weights (T elts)
ap_result	: vector recovering the estimated parameters (P elts)

This function will estimate a set of parameters (O) by minimizing the weighted residual sum of squares (WRSS) difference between the data and the model function Ô = [ X'WX ]-1 X'Wy y = data vector X = model matrix W = weights vector

Returns: 0 if success, other value otherwise.

Definition at line 1578 of file i1TCModel.cc.

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◆ ReadAndCheckConfigurationFileSpecific()

int i1TCModel::ReadAndCheckConfigurationFileSpecific ( )

virtual

This function is used to read options from a configuration file.

Returns: 0 if success, other value otherwise.

Implements vDynamicModel.

Definition at line 316 of file i1TCModel.cc.

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◆ ReadAndCheckOptionsList()

int i1TCModel::ReadAndCheckOptionsList ( string a_listOptions )

virtual

This function is used to read parameters from a string.

Parameters

const string& a_optionsList : a list of parameters separated by commas

Returns: 0 if success, other value otherwise.

Implements vDynamicModel.

Definition at line 430 of file i1TCModel.cc.

◆ RRLS()

int i1TCModel::RRLS	(	uint16_t	a_nP,
		uint16_t	a_nT,
		FLTNB **	a2p_model,
		FLTNB *	ap_data,
		FLTNB *	ap_w,
		FLTNB *	ap_result
	)

private

Non-linear least square estimator with Ridge-Regression.

Parameters

a_nP	: number of parameters (P)
a_nT	: number of data samples (T)
a2p_model	: matrix containing the model functions (TxP elts)
ap_data	: data vector (T elts)
ap_w	: vector containing the weights (T elts)
ap_result	: vector recovering the estimated parameters (P elts)

This function will estimate a set of parameters (O) by minimizing the weighted residual sum of squares (WRSS) difference between the data and the model function Ô = [ X'*W*X + t.Rw ]-1 [ X'*W*y ]

[ X'*W*X + t.Rw ]-1 [ t.Rw*Rm ] y = data vector X = model matrix W = weights vector t = Ridge constant Rw= Ridge weights Rm= Ridge means

Returns: 0 if success, other value otherwise.

Definition at line 1376 of file i1TCModel.cc.

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◆ ShowHelp()

void i1TCModel::ShowHelp ( )

virtual

Print out specific help about the implementation of the model model and its initialization.

Implements vDynamicModel.

Definition at line 201 of file i1TCModel.cc.

◆ Trapz()

int i1TCModel::Trapz	(	FLTNB *	ap_tac,
		FLTNB *	ap_citac
	)

private

return integral for each time point t (WPO_S), and cumulative integral (cumWPO_S )

Parameters

ap_tac	: vector with nb time frames elements containing the time activity curve from which integral will be computed
ap_citac	: (returned) vector with nb time frames elements recovering the cumulative integral for each time point t

Returns: 0 if success, positive value otherwise

Definition at line 1990 of file i1TCModel.cc.

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◆ WPO()

int i1TCModel::WPO	(	FLTNB *	ap_tac,
		FLTNB *	ap_citac,
		int	a_th
	)

private

return integral for each time point t (WPO_S), and cumulative integral (cumWPO_S )

Parameters

ap_tac	: vector with nb time frames elements containing the time activity curve from which integral will be computed
ap_citac	: (returned) vector with nb time frames elements recovering the cumulative integral for each time point t
a_th	: thread index

Returns: 0 if success, positive value otherwise

Definition at line 1920 of file i1TCModel.cc.

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◆ WPOinc()

FLTNB i1TCModel::WPOinc	(	uint32_t	a_time,
		FLTNB	tac,
		FLTNB	b_tac,
		FLTNB	bb_tac,
		FLTNB	n_tac
	)

private

Estimate the next integration value for a specific time point of a tac using WPO.

Parameters

a_time	: time point for which the integral will be computed
tac	: tac value at time t
b_tac	: tac value at time t-1
bb_tac	: tac value at time t-2
n_tac	: tac value at time t+1

Returns: The estimated value of the integral for this time point

Definition at line 1846 of file i1TCModel.cc.

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Member Data Documentation

◆ m2p_ct

FLTNB** i1TCModel::m2p_ct

protected

Vector containing voxel TACs (multithreaded)

Definition at line 287 of file i1TCModel.hh.

◆ m2p_cti

FLTNB** i1TCModel::m2p_cti

protected

Vector containing the integral of voxel TACs (multithreaded)

Definition at line 288 of file i1TCModel.hh.

◆ m2p_nnlsB

FLTNB** i1TCModel::m2p_nnlsB

protected

1D vector for NNLS estimation, containing the solution (multithreaded)

Definition at line 291 of file i1TCModel.hh.

◆ m2p_nnlsMat

FLTNB** i1TCModel::m2p_nnlsMat

protected

1D working vector for NNLS estimation (multithreaded)

Definition at line 292 of file i1TCModel.hh.

◆ m2p_wpoBD

FLTNB** i1TCModel::m2p_wpoBD

protected

Definition at line 306 of file i1TCModel.hh.

◆ m2p_wpoFD

FLTNB** i1TCModel::m2p_wpoFD

protected

Definition at line 305 of file i1TCModel.hh.

◆ m2p_wpoP

FLTNB** i1TCModel::m2p_wpoP

protected

Definition at line 304 of file i1TCModel.hh.

◆ m3p_nnlsA

FLTNB*** i1TCModel::m3p_nnlsA

protected

2D coefficient matrix for NNLS estimation (multithreaded)

Definition at line 290 of file i1TCModel.hh.

◆ m_intMethodFlag

bool i1TCModel::m_intMethodFlag

protected

Flag indicating the method for TACs integral computation (default=true)

Definition at line 307 of file i1TCModel.hh.

◆ m_nnlsN

uint16_t i1TCModel::m_nnlsN =3

protected

Number of parameters in NNLS/LS estimation

Definition at line 293 of file i1TCModel.hh.

◆ m_OptimisationMethodFlag

int i1TCModel::m_OptimisationMethodFlag

protected

Flag containing the optimization method

Definition at line 285 of file i1TCModel.hh.

◆ m_ridgeRegressionFlag

bool i1TCModel::m_ridgeRegressionFlag

protected

Flag indicating if ridge regression is enabled (default=false)

Definition at line 298 of file i1TCModel.hh.

◆ m_RRcst

FLTNB i1TCModel::m_RRcst

protected

Regularization parameter for ridge regression

Definition at line 297 of file i1TCModel.hh.

◆ m_savePImgFlag

bool i1TCModel::m_savePImgFlag

protected

Flag indicating if parametric images should be written on disk (default=true)

Definition at line 284 of file i1TCModel.hh.

◆ mp_DT2

FLTNB* i1TCModel::mp_DT2

protected

Vector containing the half frame time duration (for integral computation)

Definition at line 300 of file i1TCModel.hh.

◆ mp_LSden

oMatrix** i1TCModel::mp_LSden

protected

Matrix for computation (th)

Definition at line 315 of file i1TCModel.hh.

◆ mp_LSnum

oMatrix** i1TCModel::mp_LSnum

protected

Matrix for computation (th)

Definition at line 314 of file i1TCModel.hh.

◆ mp_parLowerBounds

FLTNB* i1TCModel::mp_parLowerBounds

protected

Vector containing parameters lower bound

Definition at line 296 of file i1TCModel.hh.

◆ mp_parUpperBounds

FLTNB* i1TCModel::mp_parUpperBounds

protected

Vector containing parameters upper bound

Definition at line 295 of file i1TCModel.hh.

◆ mp_RRm

oMatrix* i1TCModel::mp_RRm

protected

Ridge means

Definition at line 319 of file i1TCModel.hh.

◆ mp_RRnum

oMatrix** i1TCModel::mp_RRnum

protected

Ridge numerator for computation (th)

Definition at line 321 of file i1TCModel.hh.

◆ mp_RRw

oMatrix* i1TCModel::mp_RRw

protected

Ridge weights

Definition at line 320 of file i1TCModel.hh.

◆ mp_Theta

oMatrix** i1TCModel::mp_Theta

protected

Estimated parameters Matrix (th)

Definition at line 316 of file i1TCModel.hh.

◆ mp_VaImage

FLTNB* i1TCModel::mp_VaImage

protected

Optional input image containing the blood volume

Definition at line 323 of file i1TCModel.hh.

◆ mp_w

FLTNB* i1TCModel::mp_w

protected

Vector containing the weights for NNLS estimation

Definition at line 289 of file i1TCModel.hh.

◆ mp_wpoA

FLTNB* i1TCModel::mp_wpoA

protected

Definition at line 303 of file i1TCModel.hh.

◆ mp_wpoQ

FLTNB* i1TCModel::mp_wpoQ

protected

Definition at line 302 of file i1TCModel.hh.

◆ mp_X

oMatrix** i1TCModel::mp_X

protected

Model Matrix (threaded)

Definition at line 311 of file i1TCModel.hh.

◆ mp_Xt

oMatrix** i1TCModel::mp_Xt

protected

Matrix for computation (th)

Definition at line 312 of file i1TCModel.hh.

◆ mp_XtX

oMatrix** i1TCModel::mp_XtX

protected

Matrix for computation (th)

Definition at line 313 of file i1TCModel.hh.

◆ mp_Y

oMatrix** i1TCModel::mp_Y

protected

Data Matrix (threaded)

Definition at line 310 of file i1TCModel.hh.

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

Public Member Functions

Protected Attributes

Private Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ i1TCModel()

◆ ~i1TCModel()

Member Function Documentation

◆ CheckSpecificParameters()

◆ EstimateImageWithModel()

◆ EstimateModelParameters()

◆ EstimateModelParametersWithBF()

◆ EstimateModelParametersWithLS()

◆ EstimateModelParametersWithNNLS()

◆ InitializeSpecific()

◆ IntegrateTAC()

◆ LS()

◆ ReadAndCheckConfigurationFileSpecific()

◆ ReadAndCheckOptionsList()

◆ RRLS()

◆ ShowHelp()

◆ Trapz()

◆ WPO()

◆ WPOinc()

Member Data Documentation

◆ m2p_ct

◆ m2p_cti

◆ m2p_nnlsB

◆ m2p_nnlsMat

◆ m2p_wpoBD

◆ m2p_wpoFD

◆ m2p_wpoP

◆ m3p_nnlsA

◆ m_intMethodFlag

◆ m_nnlsN

◆ m_OptimisationMethodFlag

◆ m_ridgeRegressionFlag

◆ m_RRcst

◆ m_savePImgFlag

◆ mp_DT2

◆ mp_LSden

◆ mp_LSnum

◆ mp_parLowerBounds

◆ mp_parUpperBounds

◆ mp_RRm

◆ mp_RRnum

◆ mp_RRw

◆ mp_Theta

◆ mp_VaImage

◆ mp_w

◆ mp_wpoA

◆ mp_wpoQ

◆ mp_X

◆ mp_Xt

◆ mp_XtX

◆ mp_Y