/* fwdmodel_quipss2.h - Implements the QUIPSS II ASL model Adrian Groves, FMRIB Image Analysis Group Copyright (C) 2007 University of Oxford */ /* Part of FSL - FMRIB's Software Library http://www.fmrib.ox.ac.uk/fsl fsl@fmrib.ox.ac.uk Developed at FMRIB (Oxford Centre for Functional Magnetic Resonance Imaging of the Brain), Department of Clinical Neurology, Oxford University, Oxford, UK LICENCE FMRIB Software Library, Release 5.0 (c) 2012, The University of Oxford (the "Software") The Software remains the property of the University of Oxford ("the University"). 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Contact details are: innovation@isis.ox.ac.uk quoting reference DE/9564. */ /* fwdmodel_quipss2.h * Class declaration for the QUIPSS II ASL model used in Woolrich MRM'06 * with additional terms for nuisance regressors (affecting the signal). * Written by Adrian Groves, 2007 * FMRIB Centre, University of Oxford * * Last modified: $Date: 2007/08/02 11:16:47 $ $Author: adriang $ $Revision: 1.12 $ */ #ifndef __FABBER_FWDMODEL_QUIPSS2_H #define __FABBER_FWDMODEL_QUIPSS2_H 1 #include "fwdmodel.h" #include "inference.h" #include using namespace std; class Quipss2FwdModel : public FwdModel { public: // Virtual function overrides virtual void Evaluate(const ColumnVector& params, ColumnVector& result) const; virtual void DumpParameters(const ColumnVector& vec, const string& indents = "") const; virtual void NameParams(vector& names) const; virtual int NumParams() const { return NnStart(echoTime.Ncols()+1) + (stdevT1b>0?1:0) + (stdevInvEff>0?1:0) + (stdevDt>0?1:0) - 1; } virtual string ModelVersion() const; virtual ~Quipss2FwdModel() { return; } virtual void HardcodedInitialDists(MVNDist& prior, MVNDist& posterior) const; // Constructor Quipss2FwdModel(ArgsType& args); // Usage info static void ModelUsage(); // SimpleFwdModel(const SimpleFwdModel& from); // copy constructor - default ok? protected: // Constants // parameter lookup class: //Quipss2FwdModelIdStruct id; // This is my own rather messy way of keeping track of all my parameters. // There's probably a better way of doing it... but I haven't found it yet. int Q0index() const { return 1; } int M0index() const { return Q0index()+Qbasis.Ncols()+1; } int R0index() const { return M0index()+Mbasis.Ncols()+1; } int NnStart(int te) const { assert(te > 0 && te <= echoTime.Nrows()+1); // go one past, for getting end point return R0index()+Rbasis.Ncols()+(te-1)*Nbasis.Ncols() + 1; } int InvEffIndex() const { assert(stdevInvEff>0); return NnStart(echoTime.Ncols()+1); } int T1bIndex() const { assert(stdevT1b>0); return NnStart(echoTime.Ncols()+(stdevInvEff>0)?1:0); } int dtIndex() const { assert(stdevDt>0); return NnStart(echoTime.Ncols()+1) + (stdevT1b>0?1:0) + (stdevInvEff>0?1:0); } // Slow submatrixing... but it works. // In fact, it's plenty fast enough.. fwd model is a small part calculation time ReturnMatrix QnOf(const ColumnVector& params) const { return params.Rows(Q0index()+1,Q0index()+Qbasis.Ncols()).Evaluate(); } ReturnMatrix MnOf(const ColumnVector& params) const { return params.Rows(M0index()+1,M0index()+Mbasis.Ncols()).Evaluate(); } ReturnMatrix RnOf(const ColumnVector& params) const { return params.Rows(R0index()+1,R0index()+Rbasis.Ncols()).Evaluate(); } ReturnMatrix NnOf(int te, const ColumnVector& params) const { return params.Rows(NnStart(te),NnStart(te+1)-1).Evaluate(); } // scan parameters ColumnVector rho; ColumnVector echoTime; double TI1, TI2; // assumed known constants double fixedInvEff, fixedT1b, fixedDt; double stdevT1b, stdevInvEff, stdevDt; // >0 means treat these as parameters! // basis for each piece Matrix Qbasis; // basis in columns? Matrix Mbasis; Matrix Rbasis; Matrix Nbasis; }; #endif /* __FABBER_FWDMODEL_QUIPSS2_H */