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/*! \file eddy.cpp
\brief Contains main() and some very high level functions for eddy
*/
#pragma clang diagnostic ignored "-Wunknown-pragmas" // Ignore the OpenMP pragmas
#include <cstdlib>
#include <string>
#include <vector>
#include <cmath>
#include <boost/shared_ptr.hpp>
#include "newmat.h"
#include "newimage/newimageall.h"
#include "miscmaths/miscmaths.h"
// Disable stack_dump that upstream labels as "highly non-portable"
// one can still use plan gdb to get the same information
//#include "stack_dump.h"
#include "EddyHelperClasses.h"
#include "ECScanClasses.h"
#include "DiffusionGP.h"
#include "b0Predictor.h"
#include "EddyUtils.h"
#include "EddyCommandLineOptions.h"
using namespace EDDY;
/// Global function that registers a set of scans together
ReplacementManager Register(const EddyCommandLineOptions& clo, // Input
ScanType st, // Input
ECScanManager& sm, // Input/Output
unsigned int niter, // Input
NEWMAT::Matrix& msshist, // Output
NEWMAT::Matrix& phist); // Output
/// Global function that detect outlier slices and replaces them by their expectation
DiffStatsVector DetectAndReplaceOutliers(// Input
const EddyCommandLineOptions& clo,
ScanType st,
// Input/Output
ECScanManager& sm,
ReplacementManager& rm);
/// Global function that Loads up the prediction maker with unwarped scans
boost::shared_ptr<DWIPredictionMaker> LoadPredictionMaker(// Input
const EddyCommandLineOptions& clo,
ScanType st,
const ECScanManager& sm,
// Output
NEWIMAGE::volume<float>& mask);
/// Global function that Generates diagnostic information for subsequent analysis
void Diagnostics(const EddyCommandLineOptions& clo, // Input
unsigned int iter, // Input
ScanType st, // Input
const ECScanManager& sm, // Input
const double *mss_tmp, // Input
const DiffStatsVector& stats, // Input
NEWMAT::Matrix& mss, // Output
NEWMAT::Matrix& phist); // Output
/// The entry point of eddy.
int main(int argc, char *argv[])
{
//StackDump::Install(); // Gives us informative stack dump if/when program crashes
// Parse comand line input
EddyCommandLineOptions clo(argc,argv); // Command Line Options
// Read all available info
if (clo.Verbose()) cout << "Reading images" << endl;
ECScanManager sm(clo.ImaFname(),clo.MaskFname(),clo.AcqpFname(),clo.TopupFname(),
clo.BVecsFname(),clo.BValsFname(),clo.FirstLevelModel(),
clo.Indicies(),clo.SessionIndicies(),clo.NoOfSessions()); // Scan Manager
if (clo.Verbose() && clo.FWHM()) cout << "Smoothing images" << endl;
sm.SetFWHM(clo.FWHM());
if (clo.ResamplingMethod() == LSR) {
if (!sm.CanDoLSRResampling()) throw EddyException("These data do not support least-squares resampling");
}
// Set initial parameters. This option is only for testing/debugging/personal use
if (clo.InitFname() != std::string("")) {
if (clo.RegisterDWI() && clo.Registerb0()) sm.SetParameters(clo.InitFname(),ANY);
else if (clo.RegisterDWI()) sm.SetParameters(clo.InitFname(),DWI);
else sm.SetParameters(clo.InitFname(),B0);
}
// Do the registration
NEWMAT::Matrix dwi_mss, b0_mss, dwi_ph, b0_ph;
ReplacementManager *dwi_rm;
if (clo.NIter() && clo.RegisterDWI()) {
cout << "Running Register" << endl;
dwi_rm = new ReplacementManager(Register(clo,DWI,sm,clo.NIter(),dwi_mss,dwi_ph));
// Write outlier information
if (clo.ReplaceOutliers()) {
cout << "Running sm.GetDwi2GlobalIndexMapping" << endl;
std::vector<unsigned int> i2i = sm.GetDwi2GlobalIndexMapping();
cout << "Running dwi_rm->WriteReport" << endl;
dwi_rm->WriteReport(i2i,clo.OLReportFname());
if (clo.WriteOutlierFreeData()) {
cout << "Running sm.WriteOutlierFreeData" << endl;
sm.WriteOutlierFreeData(clo.OLFreeDataFname());
}
}
}
if (clo.NIter() && clo.Registerb0()) {
cout << "Running Register" << endl;
ReplacementManager b0_rm = Register(clo,B0,sm,clo.NIter(),b0_mss,b0_ph);
}
/*
// Write raw registration parameters (for debugging).
cout << "Running sm.WriteParameterFile for raw parameters" << endl;
sm.WriteParameterFile(clo.ParOutFname()+string(".raw"));
cout << "Running sm.WriteRegisteredImages for raw parameters" << endl;
sm.WriteRegisteredImages(clo.IOutFname()+string(".raw"),clo.ResamplingMethod());
*/
// Separate field offset from subject movement in PE direction
// if (clo.RegisterDWI()) { cout << "Running sm.SeparateFieldOffsetFromMovement" << endl; sm.SeparateFieldOffsetFromMovement(); }
// Set reference for location
if (clo.RegisterDWI()) { cout << "Running sm.SetDWIReference" << endl; sm.SetDWIReference(); }
if (clo.Registerb0()) { cout << "Running sm.Setb0Reference" << endl; sm.Setb0Reference(); }
// Write registration parameters
cout << "Running sm.WriteParameterFile" << endl;
if (clo.RegisterDWI() && clo.Registerb0()) sm.WriteParameterFile(clo.ParOutFname());
else if (clo.RegisterDWI()) sm.WriteParameterFile(clo.ParOutFname(),DWI);
else sm.WriteParameterFile(clo.ParOutFname(),B0);
// Write registered images
cout << "Running sm.WriteRegisteredImages" << endl;
if (clo.RegisterDWI() && clo.Registerb0()) sm.WriteRegisteredImages(clo.IOutFname(),clo.ResamplingMethod());
else if (clo.RegisterDWI()) sm.WriteRegisteredImages(clo.IOutFname(),clo.ResamplingMethod(),DWI);
else sm.WriteRegisteredImages(clo.IOutFname(),clo.ResamplingMethod(),B0);
// Write EC fields
cout << "Running sm.WriteECFields" << endl;
if (clo.WriteFields()) {
if (clo.RegisterDWI() && clo.Registerb0()) sm.WriteECFields(clo.ECFOutFname());
else if (clo.RegisterDWI()) sm.WriteECFields(clo.ECFOutFname(),DWI);
else sm.WriteECFields(clo.ECFOutFname(),B0);
}
if (clo.NIter() && clo.History()) {
if (clo.RegisterDWI()) {
MISCMATHS::write_ascii_matrix(clo.DwiMssHistoryFname(),dwi_mss);
MISCMATHS::write_ascii_matrix(clo.DwiParHistoryFname(),dwi_ph);
}
if (clo.Registerb0()) {
MISCMATHS::write_ascii_matrix(clo.B0MssHistoryFname(),b0_mss);
MISCMATHS::write_ascii_matrix(clo.B0ParHistoryFname(),b0_ph);
}
}
exit(EXIT_SUCCESS);
}
/****************************************************************//**
*
* A global function that registers the scans in sm.
* \param[in] clo Carries information about the command line options
* that eddy was invoked with.
* \param[in] st Specifies if we should register the diffusion weighted
* images or the b=0 images.
* \param[in,out] sm Collection of all scans. Will be updated by this call.
* \param[in] niter Specifies how many iterations should be run
* \param[out] msshist Returns the history of the mss. msshist(i,j)
* contains the mss for the jth scan on the ith iteration.
* \param[out] phist Returns the history of the estimated parameters.
* phist(i,j) contains the jth parameter on the ith iteration
* \return A ReplacementManager that details which slices in which
* scans were replaced by their expectations.
*
********************************************************************/
ReplacementManager Register(const EddyCommandLineOptions& clo, // Input
ScanType st, // Input
ECScanManager& sm, // Input/Output
unsigned int niter, // Input
NEWMAT::Matrix& msshist, // Output
NEWMAT::Matrix& phist) // Output
{
msshist.ReSize(niter,sm.NScans(st));
phist.ReSize(niter,sm.NScans(st)*sm.Scan(0,st).NParam());
double *mss_tmp = new double[sm.NScans(st)];
ReplacementManager rm(sm.NScans(st),static_cast<unsigned int>(sm.Scan(0,st).GetIma().zsize()),clo.OLNStdev(),clo.OLNVox());
NEWIMAGE::volume<float> mask = sm.Scan(0,st).GetIma(); EddyUtils::SetTrilinearInterp(mask); mask = 1.0; // Mask in model space
for (unsigned int iter=0; iter<niter; iter++) {
// Detect outliers and replace them
DiffStatsVector stats(sm.NScans(st));
if (iter && st==DWI && clo.ReplaceOutliers()) stats = DetectAndReplaceOutliers(clo,st,sm,rm);
// Load prediction maker in model space
// printf("Starting to load and evaluate predictionmaker\n");
// clock_t stime = clock();
boost::shared_ptr<DWIPredictionMaker> pmp = LoadPredictionMaker(clo,st,sm,mask);
// printf("It took %f sec to load and evaluate predictionmaker\n",double(stime-clock())/double(CLOCKS_PER_SEC));
// Calculate the parameter updates
if (clo.Verbose()) cout << "Calculating parameter updates" << endl;
// int dbl = clo.DebugLevel(); // Can't check DebugLevel inside parallel section :(
// bool vv = clo.VeryVerbose(); // Compiler crashes if I test clo.VeryVerbose() inside parallel loop :(
# pragma omp parallel for shared(mss_tmp, pmp)
for (int s=0; s<int(sm.NScans(st)); s++) {
// Get prediction in model space
NEWIMAGE::volume<float> pred = pmp->Predict(s);
// Update parameters
if (clo.DebugLevel()) {
mss_tmp[s] = EddyUtils::param_update_debug(pred,sm.GetSuscHzOffResField(),mask,ALL,true,s,iter,clo.DebugLevel(),sm.Scan(s,st),NULL);
}
else mss_tmp[s] = EddyUtils::MovAndECParamUpdate(pred,sm.GetSuscHzOffResField(),mask,true,sm.Scan(s,st));
if (clo.VeryVerbose()) printf("Iter: %d, scan: %d, mss = %f\n",iter,s,mss_tmp[s]);
}
// Print/collect some information that can be used for diagnostics
Diagnostics(clo,iter,st,sm,mss_tmp,stats,msshist,phist);
// Maybe use model based EC parameters
// if () sm.SetPredictedECParam();
}
delete [] mss_tmp;
return(rm);
}
/****************************************************************//**
*
* A global function that loads up a prediction maker with all scans
* of a given type. It will load it with unwarped scans (given the
* current estimates of the warps) as served up by sm.GetUnwarpedScan().
* \param[in] clo Carries information about the command line options
* that eddy was invoked with.
* \param[in] st Specifies if we should register the diffusion weighted
* images or the b=0 images. If it is set to DWI the function will return
* an EDDY::DiffusionGP prediction maker and if it is set to b0 it will
* return an EDDY::b0Predictor.
* \param[in] sm Collection of all scans.
* \param[out] mask Returns a mask that indicates the voxels where data
* is present for all input scans in sm.
* \return A safe pointer to a DWIPredictionMaker that can be used to
* make predictions about what the scans should look like in undistorted space.
*
********************************************************************/
boost::shared_ptr<DWIPredictionMaker> LoadPredictionMaker(// Input
const EddyCommandLineOptions& clo,
ScanType st,
const ECScanManager& sm,
// Output
NEWIMAGE::volume<float>& mask)
{
boost::shared_ptr<DWIPredictionMaker> pmp; // Prediction Maker Pointer
if (st==DWI) pmp = boost::shared_ptr<DWIPredictionMaker>(new DiffusionGP); // Gaussian Process
else pmp = boost::shared_ptr<DWIPredictionMaker>(new b0Predictor); // Silly mean predictor
pmp->SetNoOfScans(sm.NScans(st));
mask = sm.Scan(0,st).GetIma(); EddyUtils::SetTrilinearInterp(mask); mask = 1.0;
if (clo.Verbose()) cout << "Loading prediction maker";
// bool vv = clo.VeryVerbose(); // Compiler crashes if I test clo.VeryVerbose() inside parallel loop :(
if (clo.VeryVerbose()) cout << endl << "Scan: ";
#pragma omp parallel for shared(pmp,st)
for (int s=0; s<int(sm.NScans(st)); s++) {
if (clo.VeryVerbose()) printf(" %d",s);
NEWIMAGE::volume<float> tmpmask = sm.Scan(s,st).GetIma();
EddyUtils::SetTrilinearInterp(tmpmask); tmpmask = 1.0;
pmp->SetScan(sm.GetUnwarpedScan(s,tmpmask,st),sm.Scan(s,st).GetDiffPara(),s);
#pragma omp critical
{
mask *= tmpmask;
}
}
if (clo.Verbose()) cout << endl << "Evaluating prediction maker model" << endl;
pmp->EvaluateModel(sm.Mask()*mask);
return(pmp);
}
void Diagnostics(const EddyCommandLineOptions& clo, // Input
unsigned int iter, // Input
ScanType st, // Input
const ECScanManager& sm, // Input
const double *mss_tmp, // Input
const DiffStatsVector& stats, // Input
NEWMAT::Matrix& mss, // Output
NEWMAT::Matrix& phist) // Output
{
if (clo.Verbose()) {
double tss=0.0;
for (unsigned int s=0; s<sm.NScans(st); s++) tss+=mss_tmp[s];
cout << "Iter: " << iter << ", Total mss = " << tss/sm.NScans(st) << endl;
}
if (clo.History()) {
for (unsigned int s=0; s<sm.NScans(st); s++) {
mss(iter+1,s+1) = mss_tmp[s];
phist.SubMatrix(iter+1,iter+1,s*sm.Scan(0,st).NParam()+1,(s+1)*sm.Scan(0,st).NParam()) = sm.Scan(s,st).GetParams().t();
}
}
if (clo.WriteSliceStats()) {
char istring[256];
sprintf(istring,"EddySliceStatsIteration%02d",iter);
stats.Write(string(istring));
}
}
DiffStatsVector DetectAndReplaceOutliers(// Input
const EddyCommandLineOptions& clo,
ScanType st,
// Input/Output
ECScanManager& sm,
ReplacementManager& rm)
{
// printf("Entering DetectAndReplaceOutliers\n");
// Load up a prediction maker with unwarped and unsmoothed data
DWIPredictionMaker *pmp; // Prediction maker used for the outlier detection
if (st==DWI) pmp = new DiffusionGP; // Gaussian Process
else pmp = new b0Predictor; // Silly mean predictor
pmp->SetNoOfScans(sm.NScans(st));
NEWIMAGE::volume<float> mask(sm.Scan(0,st).GetIma().xsize(),sm.Scan(0,st).GetIma().ysize(),sm.Scan(0,st).GetIma().zsize());
NEWIMAGE::copybasicproperties(sm.Scan(0,st).GetIma(),mask); mask = 1.0;
// printf("Starting to load predictionmaker\n");
// clock_t stime = clock();
#pragma omp parallel for shared(pmp,st)
for (int s=0; s<int(sm.NScans(st)); s++) {
NEWIMAGE::volume<float> tmpmask(sm.Scan(s,st).GetIma().xsize(),sm.Scan(s,st).GetIma().ysize(),sm.Scan(s,st).GetIma().zsize());
NEWIMAGE::copybasicproperties(sm.Scan(s,st).GetIma(),tmpmask); tmpmask = 1.0;
pmp->SetScan(sm.GetUnwarpedOrigScan(s,tmpmask,st),sm.Scan(s,st).GetDiffPara(),s);
#pragma omp critical
{ mask *= tmpmask; }
}
// printf("It took %f sec to load pm\n",double(clock()-stime)/double(CLOCKS_PER_SEC));
// printf("Starting to evaluate the pm model\n");
// stime = clock();
pmp->EvaluateModel(sm.Mask()*mask);
// printf("It took %f sec to evaluate pm\n",double(clock()-stime)/double(CLOCKS_PER_SEC));
// Use these to generate slice-wise stats on difference between observation and prediction
// printf("Starting to generate slice-wise stats\n");
// stime = clock();
DiffStatsVector stats(sm.NScans(st));
#pragma omp parallel for shared(pmp,mask,stats,st)
for (int s=0; s<int(sm.NScans(st)); s++) {
NEWIMAGE::volume<float> pred = pmp->Predict(s);
stats[s] = EddyUtils::GetSliceWiseStats(pred,sm.GetSuscHzOffResField(),mask,sm.Mask(),sm.Scan(s,st));
}
// printf("It took %f sec to generate stats\n",double(clock()-stime)/double(CLOCKS_PER_SEC));
// stats.Write("slice_wise_stats");
// Detect outliers and update replacement manager
// printf("Updating replacement manager\n");
// stime = clock();
rm.Update(stats);
// printf("It took %f sec to update\n",double(clock()-stime)/double(CLOCKS_PER_SEC));
// Replace outlier slices with their predictions
// printf("Replacing outliers\n");
// stime = clock();
#pragma omp parallel for shared(pmp,mask,st)
for (int s=0; s<int(sm.NScans(st)); s++) {
// printf("Checking scan %d for outliers\n",s);
std::vector<unsigned int> ol = rm.OutliersInScan(s);
if (ol.size()) { // If this scan has outlier slices
// printf("Scan %d has %d outlier slices\n",s,ol.size());
NEWIMAGE::volume<float> pred = pmp->Predict(s);
sm.Scan(s,st).ReplaceSlices(pred,sm.GetSuscHzOffResField(),mask,ol);
}
}
// printf("It took %f sec to replace outliers\n",double(clock()-stime)/double(CLOCKS_PER_SEC));
// rm.DumpOutlierMap("DebugReplacementManager");
// exit(EXIT_SUCCESS);
delete pmp;
return(stats);
}
/*! \mainpage
* Here goes a description of the eddy project
*/
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