diff --git a/Modules/DiffusionImaging/FiberTracking/cmdapps/Fiberfox/FiberfoxOptimization.cpp b/Modules/DiffusionImaging/FiberTracking/cmdapps/Fiberfox/FiberfoxOptimization.cpp index 845caa9295..b7e09fb22b 100755 --- a/Modules/DiffusionImaging/FiberTracking/cmdapps/Fiberfox/FiberfoxOptimization.cpp +++ b/Modules/DiffusionImaging/FiberTracking/cmdapps/Fiberfox/FiberfoxOptimization.cpp @@ -1,383 +1,383 @@ /*=================================================================== The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center, Division of Medical and Biological Informatics. All rights reserved. This software is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See LICENSE.txt or http://www.mitk.org for details. ===================================================================*/ #include #include #include #include #include #include #include #include "mitkCommandLineParser.h" #include #include #include #include #include using namespace mitk; float CompareDwi(itk::VectorImage< short, 3 >* dwi1, itk::VectorImage< short, 3 >* dwi2) { typedef itk::VectorImage< short, 3 > DwiImageType; try{ itk::ImageRegionIterator< DwiImageType > it1(dwi1, dwi1->GetLargestPossibleRegion()); itk::ImageRegionIterator< DwiImageType > it2(dwi2, dwi2->GetLargestPossibleRegion()); unsigned int count = 0; float difference = 0; while(!it1.IsAtEnd()) { for (unsigned int i=0; iGetVectorLength(); ++i) { difference += abs(it1.Get()[i]-it2.Get()[i]); count++; } ++it1; ++it2; } return difference/count; } catch(...) { return -1; } return -1; } FiberfoxParameters MakeProposalRelaxation(FiberfoxParameters old_params, double temperature) { std::random_device r; std::default_random_engine randgen(r()); std::uniform_int_distribution uint1(0, 4); FiberfoxParameters new_params(old_params); int prop = uint1(randgen); switch(prop) { case 0: { std::normal_distribution normal_dist(0, new_params.m_SignalGen.m_SignalScale*0.1*temperature); float add = 0; while (add == 0) add = normal_dist(randgen); new_params.m_SignalGen.m_SignalScale += add; MITK_INFO << "Proposal Signal Scale: " << add << " (" << new_params.m_SignalGen.m_SignalScale << ")"; break; } case 1: { int model_index = rand()%new_params.m_NonFiberModelList.size(); double t2 = new_params.m_NonFiberModelList[model_index]->GetT2(); std::normal_distribution normal_dist(0, t2*0.1*temperature); double add = 0; while (add == 0) add = normal_dist(randgen); t2 += add; new_params.m_NonFiberModelList[model_index]->SetT2(t2); MITK_INFO << "Proposal T2 (Non-Fiber " << model_index << "): " << add << " (" << t2 << ")"; break; } case 2: { int model_index = rand()%new_params.m_FiberModelList.size(); double t2 = new_params.m_FiberModelList[model_index]->GetT2(); std::normal_distribution normal_dist(0, t2*0.1*temperature); double add = 0; while (add == 0) add = normal_dist(randgen); t2 += add; new_params.m_FiberModelList[model_index]->SetT2(t2); MITK_INFO << "Proposal T2 (Fiber " << model_index << "): " << add << " (" << t2 << ")"; break; } case 3: { int model_index = rand()%new_params.m_NonFiberModelList.size(); double t1 = new_params.m_NonFiberModelList[model_index]->GetT1(); std::normal_distribution normal_dist(0, t1*0.1*temperature); double add = 0; while (add == 0) add = normal_dist(randgen); t1 += add; new_params.m_NonFiberModelList[model_index]->SetT1(t1); MITK_INFO << "Proposal T1 (Non-Fiber " << model_index << "): " << add << " (" << t1 << ")"; break; } case 4: { int model_index = rand()%new_params.m_FiberModelList.size(); double t1 = new_params.m_FiberModelList[model_index]->GetT1(); std::normal_distribution normal_dist(0, t1*0.1*temperature); double add = 0; while (add == 0) add = normal_dist(randgen); t1 += add; new_params.m_FiberModelList[model_index]->SetT1(t1); MITK_INFO << "Proposal T1 (Fiber " << model_index << "): " << add << " (" << t1 << ")"; break; } } return new_params; } double UpdateDiffusivity(double d, double temperature) { std::random_device r; std::default_random_engine randgen(r()); std::normal_distribution normal_dist(0, d*0.1*temperature); double add = 0; while (add == 0) add = normal_dist(randgen); d += add; return d; } void ProposeDiffusivities(mitk::DiffusionSignalModel<>* signalModel, double temperature) { if (dynamic_cast*>(signalModel)) { mitk::StickModel<>* m = dynamic_cast*>(signalModel); m->SetDiffusivity(UpdateDiffusivity(m->GetDiffusivity(), temperature)); MITK_INFO << "d: " << m->GetDiffusivity(); } else if (dynamic_cast*>(signalModel)) { mitk::TensorModel<>* m = dynamic_cast*>(signalModel); m->SetDiffusivity1(UpdateDiffusivity(m->GetDiffusivity1(), temperature)); double new_d2 = UpdateDiffusivity(m->GetDiffusivity2(), temperature); - while (m->GetDiffusivity1()*0.9GetDiffusivity1()*0.2GetDiffusivity2(), temperature); m->SetDiffusivity2(new_d2); m->SetDiffusivity3(new_d2); MITK_INFO << "d1: " << m->GetDiffusivity1(); MITK_INFO << "d2: " << m->GetDiffusivity2(); MITK_INFO << "d3: " << m->GetDiffusivity3(); } else if (dynamic_cast*>(signalModel)) { mitk::BallModel<>* m = dynamic_cast*>(signalModel); m->SetDiffusivity(UpdateDiffusivity(m->GetDiffusivity(), temperature)); MITK_INFO << "d: " << m->GetDiffusivity(); } else if (dynamic_cast*>(signalModel)) { mitk::AstroStickModel<>* m = dynamic_cast*>(signalModel); m->SetDiffusivity(UpdateDiffusivity(m->GetDiffusivity(), temperature)); MITK_INFO << "d: " << m->GetDiffusivity(); } } FiberfoxParameters MakeProposalDiff(FiberfoxParameters old_params, double temperature) { std::random_device r; std::default_random_engine randgen(r()); std::uniform_int_distribution uint1(0, 1); FiberfoxParameters new_params(old_params); int prop = uint1(randgen); switch(prop) { case 0: { int model_index = rand()%new_params.m_NonFiberModelList.size(); ProposeDiffusivities( new_params.m_NonFiberModelList[model_index], temperature ); MITK_INFO << "Proposal D (Non-Fiber " << model_index << ")"; break; } case 1: { int model_index = rand()%new_params.m_FiberModelList.size(); ProposeDiffusivities( new_params.m_FiberModelList[model_index], temperature ); MITK_INFO << "Proposal D (Fiber " << model_index << ")"; break; } } return new_params; } /*! * \brief Command line interface to Fiberfox. * Simulate a diffusion-weighted image from a tractogram using the specified parameter file. */ int main(int argc, char* argv[]) { mitkCommandLineParser parser; parser.setTitle("FiberfoxOptimization"); parser.setCategory("Optimize Fiberfox Parameters"); parser.setContributor("MIC"); parser.setDescription("Command line interface to Fiberfox." " Simulate a diffusion-weighted image from a tractogram using the specified parameter file."); parser.setArgumentPrefix("--", "-"); parser.addArgument("parameters", "p", mitkCommandLineParser::InputFile, "Parameter file:", "fiberfox parameter file (.ffp)", us::Any(), false); parser.addArgument("input", "i", mitkCommandLineParser::String, "Input:", "Input tractogram or diffusion-weighted image.", us::Any(), false); parser.addArgument("template", "t", mitkCommandLineParser::String, "Template image:", "Use parameters of the template diffusion-weighted image.", us::Any(), false); parser.addArgument("iterations", "", mitkCommandLineParser::Int, "Iterations:", "Number of optimizations steps", 1000); parser.addArgument("start_temp", "", mitkCommandLineParser::Float, "Start temperature:", "", 1.0); parser.addArgument("end_temp", "", mitkCommandLineParser::Float, "End temperature:", "", 0.1); parser.addArgument("no_diff", "", mitkCommandLineParser::Bool, "Don't optimize diffusivities:", "Don't optimize diffusivities"); parser.addArgument("no_relax", "", mitkCommandLineParser::Bool, "Don't optimize relaxation times and signal scale:", "Don't optimize relaxation times and signal scale"); std::map parsedArgs = parser.parseArguments(argc, argv); if (parsedArgs.size()==0) return EXIT_FAILURE; std::string paramName = us::any_cast(parsedArgs["parameters"]); std::string input = us::any_cast(parsedArgs["input"]); int iterations=1000; if (parsedArgs.count("iterations")) iterations = us::any_cast(parsedArgs["iterations"]); float start_temp=1.0; if (parsedArgs.count("start_temp")) start_temp = us::any_cast(parsedArgs["start_temp"]); float end_temp=0.1; if (parsedArgs.count("end_temp")) end_temp = us::any_cast(parsedArgs["end_temp"]); bool no_diff=false; if (parsedArgs.count("no_diff")) no_diff = true; bool no_relax=false; if (parsedArgs.count("no_relax")) no_relax = true; if (no_relax && no_diff) { MITK_INFO << "Incompatible options. Nothing to optimize."; return EXIT_FAILURE; } FiberfoxParameters parameters; parameters.LoadParameters(paramName); MITK_INFO << "Loading template image"; typedef itk::VectorImage< short, 3 > ItkDwiType; mitk::PreferenceListReaderOptionsFunctor functor = mitk::PreferenceListReaderOptionsFunctor({"Diffusion Weighted Images", "Fiberbundles"}, {}); mitk::Image::Pointer dwi = dynamic_cast(mitk::IOUtil::Load(us::any_cast(parsedArgs["template"]), &functor)[0].GetPointer()); ItkDwiType::Pointer reference = mitk::DiffusionPropertyHelper::GetItkVectorImage(dwi); parameters.m_SignalGen.m_ImageRegion = reference->GetLargestPossibleRegion(); parameters.m_SignalGen.m_ImageSpacing = reference->GetSpacing(); parameters.m_SignalGen.m_ImageOrigin = reference->GetOrigin(); parameters.m_SignalGen.m_ImageDirection = reference->GetDirection(); parameters.SetBvalue(static_cast(dwi->GetProperty(mitk::DiffusionPropertyHelper::REFERENCEBVALUEPROPERTYNAME.c_str()).GetPointer() )->GetValue()); parameters.SetGradienDirections(static_cast( dwi->GetProperty(mitk::DiffusionPropertyHelper::GRADIENTCONTAINERPROPERTYNAME.c_str()).GetPointer() )->GetGradientDirectionsContainer()); mitk::BaseData::Pointer inputData = mitk::IOUtil::Load(input, &functor)[0]; itk::TractsToDWIImageFilter< short >::Pointer tractsToDwiFilter = itk::TractsToDWIImageFilter< short >::New(); tractsToDwiFilter->SetFiberBundle(dynamic_cast(inputData.GetPointer())); tractsToDwiFilter->SetParameters(parameters); tractsToDwiFilter->Update(); ItkDwiType::Pointer sim = tractsToDwiFilter->GetOutput(); { mitk::Image::Pointer image = mitk::GrabItkImageMemory( tractsToDwiFilter->GetOutput() ); image->GetPropertyList()->ReplaceProperty( mitk::DiffusionPropertyHelper::GRADIENTCONTAINERPROPERTYNAME.c_str(), mitk::GradientDirectionsProperty::New( parameters.m_SignalGen.GetGradientDirections() ) ); image->GetPropertyList()->ReplaceProperty( mitk::DiffusionPropertyHelper::REFERENCEBVALUEPROPERTYNAME.c_str(), mitk::FloatProperty::New( parameters.m_SignalGen.GetBvalue() ) ); mitk::DiffusionPropertyHelper propertyHelper( image ); propertyHelper.InitializeImage(); mitk::IOUtil::Save(image, "initial.dwi"); } MITK_INFO << "Iterations: " << iterations; MITK_INFO << "start_temp: " << start_temp; MITK_INFO << "end_temp: " << end_temp; double alpha = log(end_temp/start_temp); int accepted = 0; float last_diff = CompareDwi(sim, reference); for (int i=0; i<1000; ++i) { double temperature = start_temp * exp(alpha*(double)i/iterations); MITK_INFO << "Temperature: " << temperature << " (" << i+1 << "/" << iterations << ")"; std::random_device r; std::default_random_engine randgen(r()); std::uniform_int_distribution uint1(0, 1); FiberfoxParameters proposal(parameters); int select = uint1(randgen); if (no_relax) select = 0; else if (no_diff) select = 1; if (select==0) proposal = MakeProposalDiff(proposal, temperature); else proposal = MakeProposalRelaxation(proposal, temperature); std::streambuf *old = cout.rdbuf(); // <-- save std::stringstream ss; std::cout.rdbuf (ss.rdbuf()); itk::TractsToDWIImageFilter< short >::Pointer tractsToDwiFilter = itk::TractsToDWIImageFilter< short >::New(); tractsToDwiFilter->SetFiberBundle(dynamic_cast(inputData.GetPointer())); tractsToDwiFilter->SetParameters(proposal); tractsToDwiFilter->Update(); ItkDwiType::Pointer sim = tractsToDwiFilter->GetOutput(); std::cout.rdbuf (old); // <-- restore float diff = CompareDwi(sim, reference); if (last_diffGetOutput() ); image->GetPropertyList()->ReplaceProperty( mitk::DiffusionPropertyHelper::GRADIENTCONTAINERPROPERTYNAME.c_str(), mitk::GradientDirectionsProperty::New( parameters.m_SignalGen.GetGradientDirections() ) ); image->GetPropertyList()->ReplaceProperty( mitk::DiffusionPropertyHelper::REFERENCEBVALUEPROPERTYNAME.c_str(), mitk::FloatProperty::New( parameters.m_SignalGen.GetBvalue() ) ); mitk::DiffusionPropertyHelper propertyHelper( image ); propertyHelper.InitializeImage(); mitk::IOUtil::Save(image, "optimized.dwi"); proposal.SaveParameters("optimized.ffp"); std::cout.rdbuf (old); // <-- restore accepted++; MITK_INFO << "Accepted proposal (acc. rate " << (float)accepted/(i+1) << ")"; parameters = FiberfoxParameters(proposal); last_diff = diff; } MITK_INFO << "\n\n\n"; } return EXIT_SUCCESS; } diff --git a/Plugins/org.mitk.gui.qt.diffusionimaging.tractography/src/internal/QmitkStreamlineTrackingView.cpp b/Plugins/org.mitk.gui.qt.diffusionimaging.tractography/src/internal/QmitkStreamlineTrackingView.cpp index 4143969a6c..4c7efb1179 100644 --- a/Plugins/org.mitk.gui.qt.diffusionimaging.tractography/src/internal/QmitkStreamlineTrackingView.cpp +++ b/Plugins/org.mitk.gui.qt.diffusionimaging.tractography/src/internal/QmitkStreamlineTrackingView.cpp @@ -1,979 +1,981 @@ /*=================================================================== The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center, Division of Medical and Biological Informatics. All rights reserved. This software is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See LICENSE.txt or http://www.mitk.org for details. ===================================================================*/ // Blueberry #include #include #include // Qmitk #include "QmitkStreamlineTrackingView.h" #include "QmitkStdMultiWidget.h" // Qt #include // MITK #include #include #include #include #include +#include #include #include #include #include #include #include #include // VTK #include #include #include #include #include #include #include #include #include const std::string QmitkStreamlineTrackingView::VIEW_ID = "org.mitk.views.streamlinetracking"; const std::string id_DataManager = "org.mitk.views.datamanager"; using namespace berry; QmitkStreamlineTrackingWorker::QmitkStreamlineTrackingWorker(QmitkStreamlineTrackingView* view) : m_View(view) { } void QmitkStreamlineTrackingWorker::run() { m_View->m_Tracker->Update(); m_View->m_TrackingThread.quit(); } QmitkStreamlineTrackingView::QmitkStreamlineTrackingView() : m_TrackingWorker(this) , m_Controls(nullptr) , m_FirstTensorProbRun(true) , m_FirstInteractiveRun(true) , m_TrackingHandler(nullptr) , m_ThreadIsRunning(false) , m_DeleteTrackingHandler(false) , m_Visible(false) { m_TrackingWorker.moveToThread(&m_TrackingThread); connect(&m_TrackingThread, SIGNAL(started()), this, SLOT(BeforeThread())); connect(&m_TrackingThread, SIGNAL(started()), &m_TrackingWorker, SLOT(run())); connect(&m_TrackingThread, SIGNAL(finished()), this, SLOT(AfterThread())); m_TrackingTimer = new QTimer(this); } // Destructor QmitkStreamlineTrackingView::~QmitkStreamlineTrackingView() { if (m_Tracker.IsNull()) return; m_Tracker->SetStopTracking(true); m_TrackingThread.wait(); } void QmitkStreamlineTrackingView::CreateQtPartControl( QWidget *parent ) { if ( !m_Controls ) { // create GUI widgets from the Qt Designer's .ui file m_Controls = new Ui::QmitkStreamlineTrackingViewControls; m_Controls->setupUi( parent ); m_Controls->m_FaImageBox->SetDataStorage(this->GetDataStorage()); m_Controls->m_SeedImageBox->SetDataStorage(this->GetDataStorage()); m_Controls->m_MaskImageBox->SetDataStorage(this->GetDataStorage()); m_Controls->m_TargetImageBox->SetDataStorage(this->GetDataStorage()); m_Controls->m_PriorImageBox->SetDataStorage(this->GetDataStorage()); m_Controls->m_StopImageBox->SetDataStorage(this->GetDataStorage()); m_Controls->m_ForestBox->SetDataStorage(this->GetDataStorage()); m_Controls->m_ExclusionImageBox->SetDataStorage(this->GetDataStorage()); mitk::TNodePredicateDataType::Pointer isPeakImagePredicate = mitk::TNodePredicateDataType::New(); mitk::TNodePredicateDataType::Pointer isImagePredicate = mitk::TNodePredicateDataType::New(); mitk::TNodePredicateDataType::Pointer isTractographyForest = mitk::TNodePredicateDataType::New(); mitk::NodePredicateProperty::Pointer isBinaryPredicate = mitk::NodePredicateProperty::New("binary", mitk::BoolProperty::New(true)); mitk::NodePredicateNot::Pointer isNotBinaryPredicate = mitk::NodePredicateNot::New( isBinaryPredicate ); mitk::NodePredicateAnd::Pointer isNotABinaryImagePredicate = mitk::NodePredicateAnd::New( isImagePredicate, isNotBinaryPredicate ); mitk::NodePredicateDimension::Pointer dimensionPredicate = mitk::NodePredicateDimension::New(3); m_Controls->m_ForestBox->SetPredicate(isTractographyForest); m_Controls->m_FaImageBox->SetPredicate( mitk::NodePredicateAnd::New(isNotABinaryImagePredicate, dimensionPredicate) ); m_Controls->m_FaImageBox->SetZeroEntryText("--"); m_Controls->m_SeedImageBox->SetPredicate( mitk::NodePredicateAnd::New(isImagePredicate, dimensionPredicate) ); m_Controls->m_SeedImageBox->SetZeroEntryText("--"); m_Controls->m_MaskImageBox->SetPredicate( mitk::NodePredicateAnd::New(isImagePredicate, dimensionPredicate) ); m_Controls->m_MaskImageBox->SetZeroEntryText("--"); m_Controls->m_StopImageBox->SetPredicate( mitk::NodePredicateAnd::New(isImagePredicate, dimensionPredicate) ); m_Controls->m_StopImageBox->SetZeroEntryText("--"); m_Controls->m_TargetImageBox->SetPredicate( mitk::NodePredicateAnd::New(isImagePredicate, dimensionPredicate) ); m_Controls->m_TargetImageBox->SetZeroEntryText("--"); m_Controls->m_PriorImageBox->SetPredicate( isPeakImagePredicate ); m_Controls->m_PriorImageBox->SetZeroEntryText("--"); m_Controls->m_ExclusionImageBox->SetPredicate( mitk::NodePredicateAnd::New(isImagePredicate, dimensionPredicate) ); m_Controls->m_ExclusionImageBox->SetZeroEntryText("--"); connect( m_TrackingTimer, SIGNAL(timeout()), this, SLOT(TimerUpdate()) ); connect( m_Controls->commandLinkButton_2, SIGNAL(clicked()), this, SLOT(StopTractography()) ); connect( m_Controls->commandLinkButton, SIGNAL(clicked()), this, SLOT(DoFiberTracking()) ); connect( m_Controls->m_InteractiveBox, SIGNAL(stateChanged(int)), this, SLOT(ToggleInteractive()) ); connect( m_Controls->m_ModeBox, SIGNAL(currentIndexChanged(int)), this, SLOT(UpdateGui()) ); connect( m_Controls->m_FaImageBox, SIGNAL(currentIndexChanged(int)), this, SLOT(DeleteTrackingHandler()) ); connect( m_Controls->m_ModeBox, SIGNAL(currentIndexChanged(int)), this, SLOT(DeleteTrackingHandler()) ); connect( m_Controls->m_OutputProbMap, SIGNAL(stateChanged(int)), this, SLOT(OutputStyleSwitched()) ); connect( m_Controls->m_SeedImageBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_ModeBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_StopImageBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_TargetImageBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_PriorImageBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_ExclusionImageBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_MaskImageBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_FaImageBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_ForestBox, SIGNAL(currentIndexChanged(int)), this, SLOT(ForestSwitched()) ); connect( m_Controls->m_ForestBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_SeedsPerVoxelBox, SIGNAL(valueChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_NumFibersBox, SIGNAL(valueChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_ScalarThresholdBox, SIGNAL(valueChanged(double)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_OdfCutoffBox, SIGNAL(valueChanged(double)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_StepSizeBox, SIGNAL(valueChanged(double)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_SamplingDistanceBox, SIGNAL(valueChanged(double)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_AngularThresholdBox, SIGNAL(valueChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_MinTractLengthBox, SIGNAL(valueChanged(double)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_fBox, SIGNAL(valueChanged(double)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_gBox, SIGNAL(valueChanged(double)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_NumSamplesBox, SIGNAL(valueChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_SeedRadiusBox, SIGNAL(valueChanged(double)), this, SLOT(InteractiveSeedChanged()) ); connect( m_Controls->m_NumSeedsBox, SIGNAL(valueChanged(int)), this, SLOT(InteractiveSeedChanged()) ); connect( m_Controls->m_OutputProbMap, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_SharpenOdfsBox, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_InterpolationBox, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_MaskInterpolationBox, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_FlipXBox, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_FlipYBox, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_FlipZBox, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_FrontalSamplesBox, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_StopVotesBox, SIGNAL(stateChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_LoopCheckBox, SIGNAL(valueChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_TrialsPerSeedBox, SIGNAL(valueChanged(int)), this, SLOT(OnParameterChanged()) ); connect( m_Controls->m_EpConstraintsBox, SIGNAL(currentIndexChanged(int)), this, SLOT(OnParameterChanged()) ); StartStopTrackingGui(false); } UpdateGui(); } void QmitkStreamlineTrackingView::StopTractography() { if (m_Tracker.IsNull()) return; m_Tracker->SetStopTracking(true); } void QmitkStreamlineTrackingView::TimerUpdate() { if (m_Tracker.IsNull()) return; QString status_text(m_Tracker->GetStatusText().c_str()); m_Controls->m_StatusTextBox->setText(status_text); } void QmitkStreamlineTrackingView::BeforeThread() { m_TrackingTimer->start(1000); } void QmitkStreamlineTrackingView::AfterThread() { m_TrackingTimer->stop(); if (!m_Tracker->GetUseOutputProbabilityMap()) { vtkSmartPointer fiberBundle = m_Tracker->GetFiberPolyData(); if (!m_Controls->m_InteractiveBox->isChecked() && fiberBundle->GetNumberOfLines() == 0) { QMessageBox warnBox; warnBox.setWindowTitle("Warning"); warnBox.setText("No fiberbundle was generated!"); warnBox.setDetailedText("No fibers were generated using the chosen parameters. Typical reasons are:\n\n- Cutoff too high. Some images feature very low FA/GFA/peak size. Try to lower this parameter.\n- Angular threshold too strict. Try to increase this parameter.\n- A small step sizes also means many steps to go wrong. Especially in the case of probabilistic tractography. Try to adjust the angular threshold."); warnBox.setIcon(QMessageBox::Warning); warnBox.exec(); if (m_InteractivePointSetNode.IsNotNull()) m_InteractivePointSetNode->SetProperty("color", mitk::ColorProperty::New(1,1,1)); StartStopTrackingGui(false); if (m_DeleteTrackingHandler) DeleteTrackingHandler(); UpdateGui(); return; } mitk::FiberBundle::Pointer fib = mitk::FiberBundle::New(fiberBundle); fib->SetReferenceGeometry(dynamic_cast(m_ParentNode->GetData())->GetGeometry()); if (m_Controls->m_ResampleFibersBox->isChecked() && fiberBundle->GetNumberOfLines()>0) fib->Compress(m_Controls->m_FiberErrorBox->value()); fib->ColorFibersByOrientation(); m_Tracker->SetDicomProperties(fib); if (m_Controls->m_InteractiveBox->isChecked()) { if (m_InteractiveNode.IsNull()) { m_InteractiveNode = mitk::DataNode::New(); QString name("Interactive"); m_InteractiveNode->SetName(name.toStdString()); GetDataStorage()->Add(m_InteractiveNode); } m_InteractiveNode->SetData(fib); m_InteractiveNode->SetFloatProperty("Fiber2DSliceThickness", m_Tracker->GetMinVoxelSize()/2); if (auto renderWindowPart = this->GetRenderWindowPart()) renderWindowPart->RequestUpdate(); } else { mitk::DataNode::Pointer node = mitk::DataNode::New(); node->SetData(fib); QString name("FiberBundle_"); name += m_ParentNode->GetName().c_str(); name += "_Streamline"; node->SetName(name.toStdString()); node->SetFloatProperty("Fiber2DSliceThickness", m_Tracker->GetMinVoxelSize()/2); GetDataStorage()->Add(node, m_ParentNode); } } else { TrackerType::ItkDoubleImgType::Pointer outImg = m_Tracker->GetOutputProbabilityMap(); mitk::Image::Pointer img = mitk::Image::New(); img->InitializeByItk(outImg.GetPointer()); img->SetVolume(outImg->GetBufferPointer()); if (m_Controls->m_InteractiveBox->isChecked()) { if (m_InteractiveNode.IsNull()) { m_InteractiveNode = mitk::DataNode::New(); QString name("Interactive"); m_InteractiveNode->SetName(name.toStdString()); GetDataStorage()->Add(m_InteractiveNode); } m_InteractiveNode->SetData(img); mitk::LookupTable::Pointer lut = mitk::LookupTable::New(); lut->SetType(mitk::LookupTable::JET_TRANSPARENT); mitk::LookupTableProperty::Pointer lut_prop = mitk::LookupTableProperty::New(); lut_prop->SetLookupTable(lut); m_InteractiveNode->SetProperty("LookupTable", lut_prop); m_InteractiveNode->SetProperty("opacity", mitk::FloatProperty::New(0.5)); m_InteractiveNode->SetFloatProperty("Fiber2DSliceThickness", m_Tracker->GetMinVoxelSize()/2); if (auto renderWindowPart = this->GetRenderWindowPart()) renderWindowPart->RequestUpdate(); } else { mitk::DataNode::Pointer node = mitk::DataNode::New(); node->SetData(img); QString name("ProbabilityMap_"); name += m_ParentNode->GetName().c_str(); node->SetName(name.toStdString()); mitk::LookupTable::Pointer lut = mitk::LookupTable::New(); lut->SetType(mitk::LookupTable::JET_TRANSPARENT); mitk::LookupTableProperty::Pointer lut_prop = mitk::LookupTableProperty::New(); lut_prop->SetLookupTable(lut); node->SetProperty("LookupTable", lut_prop); node->SetProperty("opacity", mitk::FloatProperty::New(0.5)); GetDataStorage()->Add(node, m_ParentNode); } } if (m_InteractivePointSetNode.IsNotNull()) m_InteractivePointSetNode->SetProperty("color", mitk::ColorProperty::New(1,1,1)); StartStopTrackingGui(false); if (m_DeleteTrackingHandler) DeleteTrackingHandler(); UpdateGui(); } void QmitkStreamlineTrackingView::InteractiveSeedChanged(bool posChanged) { if (m_ThreadIsRunning || !m_Visible) return; if (!posChanged && (!m_Controls->m_InteractiveBox->isChecked() || !m_Controls->m_ParamUpdateBox->isChecked())) return; std::srand(std::time(0)); m_SeedPoints.clear(); itk::Point world_pos = this->GetRenderWindowPart()->GetSelectedPosition(); m_SeedPoints.push_back(world_pos); float radius = m_Controls->m_SeedRadiusBox->value(); int num = m_Controls->m_NumSeedsBox->value(); mitk::PointSet::Pointer pointset = mitk::PointSet::New(); pointset->InsertPoint(0, world_pos); m_InteractivePointSetNode->SetProperty("pointsize", mitk::FloatProperty::New(radius*2)); m_InteractivePointSetNode->SetProperty("point 2D size", mitk::FloatProperty::New(radius*2)); m_InteractivePointSetNode->SetData(pointset); for (int i=1; i p; p[0] = rand()%1000-500; p[1] = rand()%1000-500; p[2] = rand()%1000-500; p.Normalize(); p *= radius; m_SeedPoints.push_back(world_pos+p); } m_InteractivePointSetNode->SetProperty("color", mitk::ColorProperty::New(1,0,0)); DoFiberTracking(); } void QmitkStreamlineTrackingView::OnParameterChanged() { UpdateGui(); if (m_Controls->m_InteractiveBox->isChecked() && m_Controls->m_ParamUpdateBox->isChecked()) DoFiberTracking(); } void QmitkStreamlineTrackingView::ToggleInteractive() { UpdateGui(); m_Controls->m_SeedsPerVoxelBox->setEnabled(!m_Controls->m_InteractiveBox->isChecked()); m_Controls->m_SeedsPerVoxelLabel->setEnabled(!m_Controls->m_InteractiveBox->isChecked()); m_Controls->m_SeedImageBox->setEnabled(!m_Controls->m_InteractiveBox->isChecked()); m_Controls->label_6->setEnabled(!m_Controls->m_InteractiveBox->isChecked()); if ( m_Controls->m_InteractiveBox->isChecked() ) { if (m_FirstInteractiveRun) { QMessageBox::information(nullptr, "Information", "Place and move a spherical seed region anywhere in the image by left-clicking and dragging. If the seed region is colored red, tracking is in progress. If the seed region is colored white, tracking is finished.\nPlacing the seed region for the first time in a newly selected dataset might cause a short delay, since the tracker needs to be initialized."); m_FirstInteractiveRun = false; } QApplication::setOverrideCursor(Qt::PointingHandCursor); QApplication::processEvents(); m_InteractivePointSetNode = mitk::DataNode::New(); m_InteractivePointSetNode->SetProperty("color", mitk::ColorProperty::New(1,1,1)); m_InteractivePointSetNode->SetName("InteractiveSeedRegion"); mitk::PointSetShapeProperty::Pointer shape_prop = mitk::PointSetShapeProperty::New(); shape_prop->SetValue(mitk::PointSetShapeProperty::PointSetShape::CIRCLE); m_InteractivePointSetNode->SetProperty("Pointset.2D.shape", shape_prop); GetDataStorage()->Add(m_InteractivePointSetNode); m_SliceChangeListener.RenderWindowPartActivated(this->GetRenderWindowPart()); connect(&m_SliceChangeListener, SIGNAL(SliceChanged()), this, SLOT(OnSliceChanged())); } else { QApplication::restoreOverrideCursor(); QApplication::processEvents(); m_InteractiveNode = nullptr; m_InteractivePointSetNode = nullptr; m_SliceChangeListener.RenderWindowPartActivated(this->GetRenderWindowPart()); disconnect(&m_SliceChangeListener, SIGNAL(SliceChanged()), this, SLOT(OnSliceChanged())); } } void QmitkStreamlineTrackingView::Activated() { } void QmitkStreamlineTrackingView::Deactivated() { } void QmitkStreamlineTrackingView::Visible() { m_Visible = true; QList selection = GetDataManagerSelection(); berry::IWorkbenchPart::Pointer nullPart; OnSelectionChanged(nullPart, selection); } void QmitkStreamlineTrackingView::Hidden() { m_Visible = false; m_Controls->m_InteractiveBox->setChecked(false); ToggleInteractive(); } void QmitkStreamlineTrackingView::OnSliceChanged() { InteractiveSeedChanged(true); } void QmitkStreamlineTrackingView::SetFocus() { } void QmitkStreamlineTrackingView::DeleteTrackingHandler() { if (!m_ThreadIsRunning && m_TrackingHandler != nullptr) { delete m_TrackingHandler; m_TrackingHandler = nullptr; m_DeleteTrackingHandler = false; } else if (m_ThreadIsRunning) { m_DeleteTrackingHandler = true; } } void QmitkStreamlineTrackingView::ForestSwitched() { DeleteTrackingHandler(); } void QmitkStreamlineTrackingView::OutputStyleSwitched() { if (m_InteractiveNode.IsNotNull()) GetDataStorage()->Remove(m_InteractiveNode); m_InteractiveNode = nullptr; } void QmitkStreamlineTrackingView::OnSelectionChanged( berry::IWorkbenchPart::Pointer , const QList& nodes ) { if (!m_Visible) return; std::vector< mitk::DataNode::Pointer > last_nodes = m_InputImageNodes; m_InputImageNodes.clear(); m_InputImages.clear(); m_AdditionalInputImages.clear(); bool retrack = false; for( auto node : nodes ) { if( node.IsNotNull() && dynamic_cast(node->GetData()) ) { if( dynamic_cast(node->GetData()) ) { m_InputImageNodes.push_back(node); m_InputImages.push_back(dynamic_cast(node->GetData())); retrack = true; } else if ( dynamic_cast(node->GetData()) ) { m_InputImageNodes.push_back(node); m_InputImages.push_back(dynamic_cast(node->GetData())); retrack = true; } else if ( mitk::DiffusionPropertyHelper::IsDiffusionWeightedImage( dynamic_cast(node->GetData())) ) { m_InputImageNodes.push_back(node); m_InputImages.push_back(dynamic_cast(node->GetData())); retrack = true; } else { mitk::Image* img = dynamic_cast(node->GetData()); if (img!=nullptr) { int dim = img->GetDimension(); unsigned int* dimensions = img->GetDimensions(); if (dim==4 && dimensions[3]%3==0) { m_InputImageNodes.push_back(node); m_InputImages.push_back(dynamic_cast(node->GetData())); retrack = true; } else if (dim==3) { m_AdditionalInputImages.push_back(dynamic_cast(node->GetData())); } } } } } // sometimes the OnSelectionChanged event is sent twice and actually no selection has changed for the first event. We need to catch that. if (last_nodes.size() == m_InputImageNodes.size()) { bool same_nodes = true; for (unsigned int i=0; im_TensorImageLabel->setText("select in data-manager"); m_Controls->m_fBox->setEnabled(false); m_Controls->m_fLabel->setEnabled(false); m_Controls->m_gBox->setEnabled(false); m_Controls->m_gLabel->setEnabled(false); m_Controls->m_FaImageBox->setEnabled(true); m_Controls->mFaImageLabel->setEnabled(true); m_Controls->m_OdfCutoffBox->setEnabled(false); m_Controls->m_OdfCutoffLabel->setEnabled(false); m_Controls->m_SharpenOdfsBox->setEnabled(false); m_Controls->m_ForestBox->setVisible(false); m_Controls->m_ForestLabel->setVisible(false); m_Controls->commandLinkButton->setEnabled(false); m_Controls->m_TrialsPerSeedBox->setEnabled(false); m_Controls->m_TrialsPerSeedLabel->setEnabled(false); m_Controls->m_TargetImageBox->setVisible(false); m_Controls->m_TargetImageLabel->setVisible(false); if (m_Controls->m_InteractiveBox->isChecked()) { m_Controls->m_InteractiveSeedingFrame->setVisible(true); m_Controls->m_StaticSeedingFrame->setVisible(false); m_Controls->commandLinkButton_2->setVisible(false); m_Controls->commandLinkButton->setVisible(false); } else { m_Controls->m_InteractiveSeedingFrame->setVisible(false); m_Controls->m_StaticSeedingFrame->setVisible(true); m_Controls->commandLinkButton_2->setVisible(m_ThreadIsRunning); m_Controls->commandLinkButton->setVisible(!m_ThreadIsRunning); } if (m_Controls->m_EpConstraintsBox->currentIndex()>0) { m_Controls->m_TargetImageBox->setVisible(true); m_Controls->m_TargetImageLabel->setVisible(true); } // trials per seed are only important for probabilistic tractography if (m_Controls->m_ModeBox->currentIndex()==1) { m_Controls->m_TrialsPerSeedBox->setEnabled(true); m_Controls->m_TrialsPerSeedLabel->setEnabled(true); } if(!m_InputImageNodes.empty()) { if (m_InputImageNodes.size()>1) m_Controls->m_TensorImageLabel->setText( ( std::to_string(m_InputImageNodes.size()) + " images selected").c_str() ); else m_Controls->m_TensorImageLabel->setText(m_InputImageNodes.at(0)->GetName().c_str()); m_Controls->commandLinkButton->setEnabled(!m_Controls->m_InteractiveBox->isChecked() && !m_ThreadIsRunning); m_Controls->m_ScalarThresholdBox->setEnabled(true); m_Controls->m_FaThresholdLabel->setEnabled(true); if ( dynamic_cast(m_InputImageNodes.at(0)->GetData()) ) { m_Controls->m_fBox->setEnabled(true); m_Controls->m_fLabel->setEnabled(true); m_Controls->m_gBox->setEnabled(true); m_Controls->m_gLabel->setEnabled(true); } else if ( dynamic_cast(m_InputImageNodes.at(0)->GetData()) ) { m_Controls->m_OdfCutoffBox->setEnabled(true); m_Controls->m_OdfCutoffLabel->setEnabled(true); m_Controls->m_SharpenOdfsBox->setEnabled(true); } else if ( mitk::DiffusionPropertyHelper::IsDiffusionWeightedImage( dynamic_cast(m_InputImageNodes.at(0)->GetData())) ) { m_Controls->m_ForestBox->setVisible(true); m_Controls->m_ForestLabel->setVisible(true); m_Controls->m_ScalarThresholdBox->setEnabled(false); m_Controls->m_FaThresholdLabel->setEnabled(false); } } } void QmitkStreamlineTrackingView::StartStopTrackingGui(bool start) { m_ThreadIsRunning = start; if (!m_Controls->m_InteractiveBox->isChecked()) { m_Controls->commandLinkButton_2->setVisible(start); m_Controls->commandLinkButton->setVisible(!start); m_Controls->m_InteractiveBox->setEnabled(!start); m_Controls->m_StatusTextBox->setVisible(start); } } void QmitkStreamlineTrackingView::DoFiberTracking() { if (m_ThreadIsRunning) return; if (m_InputImages.empty()) return; if (m_Controls->m_InteractiveBox->isChecked() && m_SeedPoints.empty()) return; StartStopTrackingGui(true); m_Tracker = TrackerType::New(); if( dynamic_cast(m_InputImageNodes.at(0)->GetData()) ) { typedef mitk::ImageToItk CasterType; if (m_Controls->m_ModeBox->currentIndex()==1) { if (m_InputImages.size()>1) { QMessageBox::information(nullptr, "Information", "Probabilistic tensor tractography is only implemented for single-tensor mode!"); StartStopTrackingGui(false); return; } // if (m_FirstTensorProbRun) // { // QMessageBox::information(nullptr, "Information", "Internally calculating ODF from tensor image and performing probabilistic ODF tractography. ODFs are sharpened (min-max normalized and raised to the power of 4). TEND parameters are ignored."); // m_FirstTensorProbRun = false; // } if (m_TrackingHandler==nullptr) { typedef mitk::ImageToItk< mitk::TrackingHandlerOdf::ItkOdfImageType > CasterType; m_TrackingHandler = new mitk::TrackingHandlerOdf(); mitk::TensorImage::ItkTensorImageType::Pointer itkImg = mitk::TensorImage::ItkTensorImageType::New(); mitk::CastToItkImage(m_InputImages.at(0), itkImg); typedef itk::TensorImageToOdfImageFilter< float, float > FilterType; FilterType::Pointer filter = FilterType::New(); filter->SetInput( itkImg ); filter->Update(); dynamic_cast(m_TrackingHandler)->SetOdfImage(filter->GetOutput()); if (m_Controls->m_FaImageBox->GetSelectedNode().IsNotNull()) { ItkFloatImageType::Pointer itkImg = ItkFloatImageType::New(); mitk::CastToItkImage(dynamic_cast(m_Controls->m_FaImageBox->GetSelectedNode()->GetData()), itkImg); dynamic_cast(m_TrackingHandler)->SetGfaImage(itkImg); } } dynamic_cast(m_TrackingHandler)->SetGfaThreshold(m_Controls->m_ScalarThresholdBox->value()); dynamic_cast(m_TrackingHandler)->SetOdfThreshold(0); dynamic_cast(m_TrackingHandler)->SetSharpenOdfs(true); dynamic_cast(m_TrackingHandler)->SetIsOdfFromTensor(true); } else { if (m_TrackingHandler==nullptr) { m_TrackingHandler = new mitk::TrackingHandlerTensor(); for (int i=0; i<(int)m_InputImages.size(); i++) { typedef mitk::ImageToItk< mitk::TrackingHandlerTensor::ItkTensorImageType > CasterType; CasterType::Pointer caster = CasterType::New(); caster->SetInput(m_InputImages.at(i)); caster->Update(); mitk::TrackingHandlerTensor::ItkTensorImageType::ConstPointer itkImg = caster->GetOutput(); dynamic_cast(m_TrackingHandler)->AddTensorImage(itkImg); } if (m_Controls->m_FaImageBox->GetSelectedNode().IsNotNull()) { ItkFloatImageType::Pointer itkImg = ItkFloatImageType::New(); mitk::CastToItkImage(dynamic_cast(m_Controls->m_FaImageBox->GetSelectedNode()->GetData()), itkImg); dynamic_cast(m_TrackingHandler)->SetFaImage(itkImg); } } dynamic_cast(m_TrackingHandler)->SetFaThreshold(m_Controls->m_ScalarThresholdBox->value()); dynamic_cast(m_TrackingHandler)->SetF((float)m_Controls->m_fBox->value()); dynamic_cast(m_TrackingHandler)->SetG((float)m_Controls->m_gBox->value()); } } else if ( dynamic_cast(m_InputImageNodes.at(0)->GetData()) ) { if (m_TrackingHandler==nullptr) { typedef mitk::ImageToItk< mitk::TrackingHandlerOdf::ItkOdfImageType > CasterType; m_TrackingHandler = new mitk::TrackingHandlerOdf(); mitk::TrackingHandlerOdf::ItkOdfImageType::Pointer itkImg = mitk::TrackingHandlerOdf::ItkOdfImageType::New(); mitk::CastToItkImage(m_InputImages.at(0), itkImg); dynamic_cast(m_TrackingHandler)->SetOdfImage(itkImg); if (m_Controls->m_FaImageBox->GetSelectedNode().IsNotNull()) { ItkFloatImageType::Pointer itkImg = ItkFloatImageType::New(); mitk::CastToItkImage(dynamic_cast(m_Controls->m_FaImageBox->GetSelectedNode()->GetData()), itkImg); dynamic_cast(m_TrackingHandler)->SetGfaImage(itkImg); } } dynamic_cast(m_TrackingHandler)->SetGfaThreshold(m_Controls->m_ScalarThresholdBox->value()); dynamic_cast(m_TrackingHandler)->SetOdfThreshold(m_Controls->m_OdfCutoffBox->value()); dynamic_cast(m_TrackingHandler)->SetSharpenOdfs(m_Controls->m_SharpenOdfsBox->isChecked()); } else if ( mitk::DiffusionPropertyHelper::IsDiffusionWeightedImage( dynamic_cast(m_InputImageNodes.at(0)->GetData())) ) { if ( m_Controls->m_ForestBox->GetSelectedNode().IsNull() ) { QMessageBox::information(nullptr, "Information", "Not random forest for machine learning based tractography (raw dMRI tractography) selected. Did you accidentally select the raw diffusion-weighted image in the datamanager?"); StartStopTrackingGui(false); return; } if (m_TrackingHandler==nullptr) { mitk::TractographyForest::Pointer forest = dynamic_cast(m_Controls->m_ForestBox->GetSelectedNode()->GetData()); mitk::Image::Pointer dwi = dynamic_cast(m_InputImageNodes.at(0)->GetData()); std::vector< std::vector< ItkFloatImageType::Pointer > > additionalFeatureImages; additionalFeatureImages.push_back(std::vector< ItkFloatImageType::Pointer >()); for (auto img : m_AdditionalInputImages) { ItkFloatImageType::Pointer itkimg = ItkFloatImageType::New(); mitk::CastToItkImage(img, itkimg); additionalFeatureImages.at(0).push_back(itkimg); } bool forest_valid = false; if (forest->GetNumFeatures()>=100) { int num_previous_directions = (forest->GetNumFeatures() - (100 + additionalFeatureImages.at(0).size()))/3; m_TrackingHandler = new mitk::TrackingHandlerRandomForest<6, 100>(); dynamic_cast*>(m_TrackingHandler)->AddDwi(dwi); dynamic_cast*>(m_TrackingHandler)->SetAdditionalFeatureImages(additionalFeatureImages); dynamic_cast*>(m_TrackingHandler)->SetForest(forest); dynamic_cast*>(m_TrackingHandler)->SetNumPreviousDirections(num_previous_directions); forest_valid = dynamic_cast*>(m_TrackingHandler)->IsForestValid(); } else { int num_previous_directions = (forest->GetNumFeatures() - (28 + additionalFeatureImages.at(0).size()))/3; m_TrackingHandler = new mitk::TrackingHandlerRandomForest<6, 28>(); dynamic_cast*>(m_TrackingHandler)->AddDwi(dwi); dynamic_cast*>(m_TrackingHandler)->SetAdditionalFeatureImages(additionalFeatureImages); dynamic_cast*>(m_TrackingHandler)->SetForest(forest); dynamic_cast*>(m_TrackingHandler)->SetNumPreviousDirections(num_previous_directions); forest_valid = dynamic_cast*>(m_TrackingHandler)->IsForestValid(); } if (!forest_valid) { QMessageBox::information(nullptr, "Information", "Random forest is invalid. The forest signatue does not match the parameters of TrackingHandlerRandomForest."); StartStopTrackingGui(false); return; } } } else { if (m_Controls->m_ModeBox->currentIndex()==1) { QMessageBox::information(nullptr, "Information", "Probabilstic tractography is not implemented for peak images."); StartStopTrackingGui(false); return; } try { if (m_TrackingHandler==nullptr) { typedef mitk::ImageToItk< mitk::TrackingHandlerPeaks::PeakImgType > CasterType; CasterType::Pointer caster = CasterType::New(); caster->SetInput(m_InputImages.at(0)); + caster->SetCopyMemFlag(true); caster->Update(); mitk::TrackingHandlerPeaks::PeakImgType::Pointer itkImg = caster->GetOutput(); m_TrackingHandler = new mitk::TrackingHandlerPeaks(); dynamic_cast(m_TrackingHandler)->SetPeakImage(itkImg); } dynamic_cast(m_TrackingHandler)->SetPeakThreshold(m_Controls->m_ScalarThresholdBox->value()); } catch(...) { QMessageBox::information(nullptr, "Error", "Peak tracker could not be initialized. Is your input image in the correct format (4D float image, peaks in the 4th dimension)?"); StartStopTrackingGui(false); return; } } m_TrackingHandler->SetFlipX(m_Controls->m_FlipXBox->isChecked()); m_TrackingHandler->SetFlipY(m_Controls->m_FlipYBox->isChecked()); m_TrackingHandler->SetFlipZ(m_Controls->m_FlipZBox->isChecked()); m_TrackingHandler->SetInterpolate(m_Controls->m_InterpolationBox->isChecked()); switch (m_Controls->m_ModeBox->currentIndex()) { case 0: m_TrackingHandler->SetMode(mitk::TrackingDataHandler::MODE::DETERMINISTIC); break; case 1: m_TrackingHandler->SetMode(mitk::TrackingDataHandler::MODE::PROBABILISTIC); break; default: m_TrackingHandler->SetMode(mitk::TrackingDataHandler::MODE::DETERMINISTIC); } if (m_Controls->m_InteractiveBox->isChecked()) { m_Tracker->SetSeedPoints(m_SeedPoints); } else if (m_Controls->m_SeedImageBox->GetSelectedNode().IsNotNull()) { ItkFloatImageType::Pointer mask = ItkFloatImageType::New(); mitk::CastToItkImage(dynamic_cast(m_Controls->m_SeedImageBox->GetSelectedNode()->GetData()), mask); m_Tracker->SetSeedImage(mask); } if (m_Controls->m_MaskImageBox->GetSelectedNode().IsNotNull()) { ItkFloatImageType::Pointer mask = ItkFloatImageType::New(); mitk::CastToItkImage(dynamic_cast(m_Controls->m_MaskImageBox->GetSelectedNode()->GetData()), mask); m_Tracker->SetMaskImage(mask); } if (m_Controls->m_StopImageBox->GetSelectedNode().IsNotNull()) { ItkFloatImageType::Pointer mask = ItkFloatImageType::New(); mitk::CastToItkImage(dynamic_cast(m_Controls->m_StopImageBox->GetSelectedNode()->GetData()), mask); m_Tracker->SetStoppingRegions(mask); } if (m_Controls->m_TargetImageBox->GetSelectedNode().IsNotNull()) { ItkFloatImageType::Pointer mask = ItkFloatImageType::New(); mitk::CastToItkImage(dynamic_cast(m_Controls->m_TargetImageBox->GetSelectedNode()->GetData()), mask); m_Tracker->SetTargetRegions(mask); } if (m_Controls->m_PriorImageBox->GetSelectedNode().IsNotNull()) { typedef mitk::ImageToItk< mitk::TrackingHandlerPeaks::PeakImgType > CasterType; CasterType::Pointer caster = CasterType::New(); caster->SetInput(dynamic_cast(m_Controls->m_PriorImageBox->GetSelectedNode()->GetData())); + caster->SetCopyMemFlag(true); caster->Update(); mitk::TrackingHandlerPeaks::PeakImgType::Pointer itkImg = caster->GetOutput(); mitk::TrackingDataHandler* trackingPriorHandler = new mitk::TrackingHandlerPeaks(); dynamic_cast(trackingPriorHandler)->SetPeakImage(itkImg); dynamic_cast(trackingPriorHandler)->SetPeakThreshold(m_Controls->m_ScalarThresholdBox->value()); trackingPriorHandler->SetFlipX(m_Controls->m_FlipXBox->isChecked()); trackingPriorHandler->SetFlipY(m_Controls->m_FlipYBox->isChecked()); trackingPriorHandler->SetFlipZ(m_Controls->m_FlipZBox->isChecked()); trackingPriorHandler->SetInterpolate(m_Controls->m_InterpolationBox->isChecked()); trackingPriorHandler->SetMode(mitk::TrackingDataHandler::MODE::DETERMINISTIC); - trackingPriorHandler->SetAngularThreshold(0.0); m_Tracker->SetTrackingPriorHandler(trackingPriorHandler); m_Tracker->SetTrackingPriorWeight(m_Controls->m_PriorWeightBox->value()); m_Tracker->SetTrackingPriorAsMask(m_Controls->m_PriorAsMaskBox->isChecked()); m_Tracker->SetIntroduceDirectionsFromPrior(m_Controls->m_NewDirectionsFromPriorBox->isChecked()); } if (m_Controls->m_ExclusionImageBox->GetSelectedNode().IsNotNull()) { ItkFloatImageType::Pointer mask = ItkFloatImageType::New(); mitk::CastToItkImage(dynamic_cast(m_Controls->m_ExclusionImageBox->GetSelectedNode()->GetData()), mask); m_Tracker->SetExclusionRegions(mask); } // Endpoint constraints switch (m_Controls->m_EpConstraintsBox->currentIndex()) { case 0: m_Tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::NONE); m_Tracker->SetTargetRegions(nullptr); break; case 1: m_Tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::EPS_IN_TARGET); break; case 2: m_Tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::EPS_IN_TARGET_LABELDIFF); break; case 3: m_Tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::EPS_IN_SEED_AND_TARGET); break; case 4: m_Tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::MIN_ONE_EP_IN_TARGET); break; case 5: m_Tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::ONE_EP_IN_TARGET); break; case 6: m_Tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::NO_EP_IN_TARGET); break; } if (m_Tracker->GetEndpointConstraint()!=itk::StreamlineTrackingFilter::EndpointConstraints::NONE && m_Controls->m_TargetImageBox->GetSelectedNode().IsNull()) { QMessageBox::information(nullptr, "Error", "Endpoint constraints are used but no target image is set!"); StartStopTrackingGui(false); return; } else if (m_Tracker->GetEndpointConstraint()==itk::StreamlineTrackingFilter::EndpointConstraints::EPS_IN_SEED_AND_TARGET && (m_Controls->m_SeedImageBox->GetSelectedNode().IsNull()|| m_Controls->m_TargetImageBox->GetSelectedNode().IsNull()) ) { QMessageBox::information(nullptr, "Error", "Endpoint constraint EPS_IN_SEED_AND_TARGET is used but no target or no seed image is set!"); StartStopTrackingGui(false); return; } m_Tracker->SetInterpolateMasks(m_Controls->m_MaskInterpolationBox->isChecked()); m_Tracker->SetVerbose(!m_Controls->m_InteractiveBox->isChecked()); m_Tracker->SetSeedsPerVoxel(m_Controls->m_SeedsPerVoxelBox->value()); m_Tracker->SetStepSize(m_Controls->m_StepSizeBox->value()); m_Tracker->SetSamplingDistance(m_Controls->m_SamplingDistanceBox->value()); m_Tracker->SetUseStopVotes(m_Controls->m_StopVotesBox->isChecked()); m_Tracker->SetOnlyForwardSamples(m_Controls->m_FrontalSamplesBox->isChecked()); m_Tracker->SetTrialsPerSeed(m_Controls->m_TrialsPerSeedBox->value()); m_Tracker->SetMaxNumTracts(m_Controls->m_NumFibersBox->value()); m_Tracker->SetNumberOfSamples(m_Controls->m_NumSamplesBox->value()); m_Tracker->SetTrackingHandler(m_TrackingHandler); m_Tracker->SetLoopCheck(m_Controls->m_LoopCheckBox->value()); m_Tracker->SetAngularThreshold(m_Controls->m_AngularThresholdBox->value()); m_Tracker->SetMinTractLength(m_Controls->m_MinTractLengthBox->value()); m_Tracker->SetUseOutputProbabilityMap(m_Controls->m_OutputProbMap->isChecked()); m_ParentNode = m_InputImageNodes.at(0); m_TrackingThread.start(QThread::LowestPriority); } diff --git a/Plugins/org.mitk.gui.qt.diffusionimaging.tractography/src/internal/QmitkStreamlineTrackingViewControls.ui b/Plugins/org.mitk.gui.qt.diffusionimaging.tractography/src/internal/QmitkStreamlineTrackingViewControls.ui index 43b054e67e..9831116227 100644 --- a/Plugins/org.mitk.gui.qt.diffusionimaging.tractography/src/internal/QmitkStreamlineTrackingViewControls.ui +++ b/Plugins/org.mitk.gui.qt.diffusionimaging.tractography/src/internal/QmitkStreamlineTrackingViewControls.ui @@ -1,1560 +1,1560 @@ QmitkStreamlineTrackingViewControls 0 0 453 859 0 0 QmitkTemplate 3 3 0 40 QFrame::NoFrame QFrame::Raised 0 15 0 0 6 15 true 0 0 true QFrame::NoFrame QFrame::Raised 0 0 0 0 Input Image. ODF, tensor and peak images are currently supported. Input Image: Input Image. ODF, tensor, peak, and, in case of ML tractography, raw diffusion-weighted images are currently supported. <html><head/><body><p><span style=" color:#ff0000;">select image in data-manager</span></p></body></html> true Tractography Forest: Random forest for machine learning based tractography. QComboBox::AdjustToMinimumContentsLength - true Stop tractography and return all fibers reconstructed until now. Stop Tractography false Start Tractography 0 0 0 0 0 0 0 421 267 Seeding Specify how, where and how many tractography seed points are placed. QFrame::NoFrame QFrame::Raised 0 0 0 0 QFrame::NoFrame QFrame::Raised 0 0 0 0 Number of seed points equally distributed around selected position. 1 9999999 50 Radius: Seedpoints are equally distributed within a sphere centered at the selected position with the specified radius (in mm). 2 50.000000000000000 0.100000000000000 2.000000000000000 Num. Seeds: true When checked, parameter changes cause instant retracking while in interactive mode. Update on Parameter Change true QFrame::NoFrame QFrame::Raised 0 0 0 0 Try each seed N times until a valid streamline is obtained (only for probabilistic tractography). Minimum fiber length (in mm) 1 999 10 Trials Per Seed: Max. Num. Fibers: Tractography is stopped after the desired number of fibers is reached, even before all seed points are processed (-1 means no limit). -1 999999999 -1 QFrame::NoFrame QFrame::Raised 0 0 0 0 Number of seed points placed in each voxel. 1 9999999 Seeds per Voxel: Seed points are only placed inside the regions defined in the seed image. If no seed image is selected, the whole image is seeded. QComboBox::AdjustToMinimumContentsLength - Seed Image: true Dynamically pick a seed location by click into image. Enable Interactive Tractography Qt::Vertical 20 40 0 0 435 224 ROI Constraints Specify various ROI and mask images to constrain the tractography process. Mask Image: Fibers that enter a region defined in this image will stop immediately. QComboBox::AdjustToMinimumContentsLength - Select which fibers should be accepted or rejected based on the location of their endpoints. QComboBox::AdjustToMinimumContentsLength No Constraints on EP locations Both EPs in Target Image Both EPs in Target Image But Different Label One EP in Seed Image and One EP in Target Image At Least One EP in Target Image Exactly One EP in Target Image No EP in Target Image Endpoint Constraints: Stop ROI Image: The target image is used for the endpoint constraint strategy defined above. QComboBox::AdjustToMinimumContentsLength - Exclusion ROI Image: Fibers that leave the regions defined in this image will stop immediately. QComboBox::AdjustToMinimumContentsLength - Target ROI Image: Fibers that enter a region defined in this image will be discarded. QComboBox::AdjustToMinimumContentsLength - Qt::Vertical 20 40 0 0 421 359 Tractography Parameters Specify the behavior of the tractography at each streamline integration step (step size, deterministic/probabilistic, ...). Qt::Vertical 20 40 f=1 + g=0 means FACT (depending on the chosen interpolation). f=0 and g=1 means TEND (disable interpolation for this mode!). 2 1.000000000000000 0.100000000000000 0.000000000000000 Toggle between deterministic and probabilistic tractography. Some modes might not be available for all types of tractography. Deterministic Probabilistic Cutoff: FA/GFA Image: Mode: Angular Threshold: Step size (in voxels) 2 0.010000000000000 10.000000000000000 0.100000000000000 0.500000000000000 Maximum allowed angular SDTEV over 4 voxel lengths. Default: no loop check. -1 180 -1 If an image is selected, the stopping criterion is not calculated from the input image but instead the selected image is used. QComboBox::AdjustToMinimumContentsLength - Step Size: Additional threshold on the ODF magnitude. This is useful in case of CSD fODF tractography. For fODFs a good default value is 0.1, for normalized dODFs, e.g. Q-ball ODFs, this threshold should be very low (0.00025) or 0. 5 1.000000000000000 0.100000000000000 0.000250000000000 f=1 + g=0 means FACT (depending on the chosen interpolation). f=0 and g=1 means TEND (disable interpolation for this mode!). 2 1.000000000000000 0.100000000000000 1.000000000000000 If you are using dODF images as input, it is advisable to sharpen the ODFs (min-max normalize and raise to the power of 4). This is not necessary for CSD fODFs, since they are naturally much sharper. f parameter of tensor tractography. f=1 + g=0 means FACT (depending on the chosen interpolation). f=0 and g=1 means TEND (disable interpolation for this mode!). f: Min. Tract Length: Threshold on peak magnitude, FA, GFA, ... 5 1.000000000000000 0.100000000000000 0.100000000000000 ODF Cutoff: Minimum tract length in mm. Shorter fibers are discarded. Minimum fiber length (in mm) 1 999.000000000000000 1.000000000000000 20.000000000000000 Loop Check: Angular threshold between two steps (in degree). Default: 90° * step_size -1 90 1 -1 g: Sharpen ODFs: 0 0 435 224 Tractography Prior Restrict to Prior: Weight: Peak Image: Weighting factor between prior and data. 1.000000000000000 0.100000000000000 0.500000000000000 Restrict tractography to regions where the prior is valid. true Qt::Vertical 20 40 New Directions From Prior: If unchecked, the prior cannot create directions where there are none in the data. - true + false 0 0 435 224 Neighborhood Sampling Specify if and how information about the current streamline neighborhood should be used. Only neighborhood samples in front of the current streamline position are considered. Use Only Frontal Samples false If checked, the majority of sampling points has to place a stop-vote for the streamline to terminate. If not checked, all sampling positions have to vote for a streamline termination. Use Stop-Votes false QFrame::NoFrame QFrame::Raised 0 0 0 0 Num. Samples: Number of neighborhood samples that are used to determine the next fiber progression direction. 50 Sampling Distance: Sampling distance (in voxels) 2 10.000000000000000 0.100000000000000 0.250000000000000 Qt::Vertical 20 40 0 0 435 224 Data Handling Specify interpolation and direction flips. QFrame::NoFrame QFrame::Raised 0 0 0 0 Trilinearly interpolate the input image used for tractography. Interpolate Tractography Data true Trilinearly interpolate the ROI images used to constrain the tractography. Interpolate ROI Images true QFrame::NoFrame QFrame::Raised 0 0 0 0 QFrame::NoFrame QFrame::Raised 0 0 0 0 Internally flips progression directions. This might be necessary depending on the input data. x Internally flips progression directions. This might be necessary depending on the input data. y Internally flips progression directions. This might be necessary depending on the input data. z Flip directions: Qt::Vertical 20 40 0 0 435 224 Output and Postprocessing Specify the tractography output (streamlines or probability maps) and postprocessing steps. QFrame::NoFrame QFrame::Raised 0 0 0 0 Compress fibers using the specified error constraint. Compress Fibers true Qt::StrongFocus Lossy fiber compression. Recommended for large tractograms. Maximum error in mm. 3 10.000000000000000 0.010000000000000 0.100000000000000 Output map with voxel-wise visitation counts instead of streamlines. Output Probability Map false Qt::Vertical 20 40 QmitkDataStorageComboBox QComboBox
QmitkDataStorageComboBox.h
 QmitkDataStorageComboBoxWithSelectNone QComboBox
QmitkDataStorageComboBoxWithSelectNone.h