/* FAST4 - FMRIB's Automated Segmentation Tool v4 John Vickers, Mark Jenkinson, Steve Smith and Matthew Webster FMRIB Image Analysis Group Copyright (C) 2005-2009 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"). The Software is distributed "AS IS" under this Licence solely for non-commercial use in the hope that it will be useful, but in order that the University as a charitable foundation protects its assets for the benefit of its educational and research purposes, the University makes clear that no condition is made or to be implied, nor is any warranty given or to be implied, as to the accuracy of the Software, or that it will be suitable for any particular purpose or for use under any specific conditions. Furthermore, the University disclaims all responsibility for the use which is made of the Software. It further disclaims any liability for the outcomes arising from using the Software. The Licensee agrees to indemnify the University and hold the University harmless from and against any and all claims, damages and liabilities asserted by third parties (including claims for negligence) which arise directly or indirectly from the use of the Software or the sale of any products based on the Software. No part of the Software may be reproduced, modified, transmitted or transferred in any form or by any means, electronic or mechanical, without the express permission of the University. The permission of the University is not required if the said reproduction, modification, transmission or transference is done without financial return, the conditions of this Licence are imposed upon the receiver of the product, and all original and amended source code is included in any transmitted product. You may be held legally responsible for any copyright infringement that is caused or encouraged by your failure to abide by these terms and conditions. You are not permitted under this Licence to use this Software commercially. Use for which any financial return is received shall be defined as commercial use, and includes (1) integration of all or part of the source code or the Software into a product for sale or license by or on behalf of Licensee to third parties or (2) use of the Software or any derivative of it for research with the final aim of developing software products for sale or license to a third party or (3) use of the Software or any derivative of it for research with the final aim of developing non-software products for sale or license to a third party, or (4) use of the Software to provide any service to an external organisation for which payment is received. If you are interested in using the Software commercially, please contact Isis Innovation Limited ("Isis"), the technology transfer company of the University, to negotiate a licence. Contact details are: innovation@isis.ox.ac.uk quoting reference DE/9564. */ #include "newimage/newimageall.h" #include "miscmaths/miscmaths.h" #include "utils/options.h" #include class ZMRISegmentation { public: ZMRISegmentation(); ~ZMRISegmentation() { } void TanakaCreate(const NEWIMAGE::volume& image, float fbeta, int nclasses, float nblowpass, bool bbias, int biterationspve, float mixeltypeMRF, int nbiter, int initinitfixed, int winitfixed, int bapused, float hyp, bool verb,string mansegfle,int typeoffile); int TanakaMain(NEWIMAGE::volume& pcsf, NEWIMAGE::volume& pgm, NEWIMAGE::volume& pwm); NEWIMAGE::volume4D members; NEWIMAGE::volume4D m_post; NEWIMAGE::volume4D m_pve; NEWIMAGE::volume m_BiasField; NEWIMAGE::volume m_Segment; NEWIMAGE::volume m_pveSegment; NEWIMAGE::volumehardPV; private: void BiasRemoval(); void Classification(); void Classification(int x, int y, int z); NEWIMAGE::volume Convolve(NEWIMAGE::volume& resfieldimage); void Dimensions(); void Initclass(); float MRFWeightsTotal(); double MRFWeightsInner(const int x, const int y, const int z,const int c); double MRFWeightsAM(const int l, const int m, const int n); float logGaussian(float y_i, float mu, float sigma); float PVEnergy(int x, int y, int z, float mu, float sigma); void qsort(); void TanakaIterations(); void TanakaHyper(); void TanakaPriorHyper(); void Initialise(); void InitSimple(const NEWIMAGE::volume& pcsf, const NEWIMAGE::volume& pgm, const NEWIMAGE::volume& pwm); void UpdateMembers(NEWIMAGE::volume4D& probability); void WeightedKMeans(); void pveIterations(); void pveInitialize(); void takeexpo(); void InitKernel(float kernalsize); void pveClassification(int x, int y, int z); void pveClassification(); void Probabilities(int index); void calculateVolumes(const NEWIMAGE::volume4D& probs); void printVolumeTotals(); void PVClassificationStep(); void ICMPV(); void PVEnergyInit(); void PVestimation(); void MeansVariances(int numberofclasses, NEWIMAGE::volume4D& probability); NEWIMAGE::volume4DPVprob; NEWIMAGE::volume4D pvprobsinit; NEWIMAGE::volume4D talpriors; NEWIMAGE:: volume4D m_prob; NEWIMAGE::volume m_Mricopy; NEWIMAGE::volume m_Mri; NEWIMAGE::volume m_mask; ColumnVector kernelx, kernely, kernelz; vector volumequant; vector m_mean; vector m_variance; vector weight; vector rhs; double m_nxdim, m_nydim, m_nzdim; float m_nbLowpass; float beta; float pveBmixeltype; float nvoxel; float Hyper; float amx, amy, amz, amxy, amzy, amzx; int imagetype,m_nWidth, m_nHeight, m_nDepth; int neighbour[27]; int m_nbIter; int bapusedflag; int nClasses; int inititerations; int usingmeanfield; int iterationspve; int initfixed; bool biasfieldremoval; bool verboseusage; string mansegfile; class kmeansexception: public exception { public: virtual const char* what() const throw () { return "Exception: Not enough classes detected to init KMeans"; } } kmeansexc; };