diff --git a/Modules/ModelFit/cmdapps/Fuse3Dto4DImageMiniApp.cpp b/Modules/ModelFit/cmdapps/Fuse3Dto4DImageMiniApp.cpp index a2cd40129f..de03cf4055 100644 --- a/Modules/ModelFit/cmdapps/Fuse3Dto4DImageMiniApp.cpp +++ b/Modules/ModelFit/cmdapps/Fuse3Dto4DImageMiniApp.cpp @@ -1,167 +1,167 @@ /*============================================================================ The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center (DKFZ) All rights reserved. Use of this source code is governed by a 3-clause BSD license that can be found in the LICENSE file. ============================================================================*/ // std includes #include #include // itk includes #include "itksys/SystemTools.hxx" // CTK includes #include "mitkCommandLineParser.h" // MITK includes #include #include #include mitkCommandLineParser::StringContainerType inFilenames; std::string outFileName; std::vector images; std::vector timebounds; void setupParser(mitkCommandLineParser& parser) { // set general information about your MiniApp parser.setCategory("Dynamic Data Analysis Tools"); parser.setTitle("Fuse 3D to 4D Image"); parser.setDescription("MiniApp that allows to fuse several 3D images (with same geometry) into a 3D+t (4D) image that can be processed as dynamic data."); parser.setContributor("DKFZ MIC"); //! [create parser] //! [add arguments] // how should arguments be prefixed parser.setArgumentPrefix("--", "-"); // add each argument, unless specified otherwise each argument is optional // see mitkCommandLineParser::addArgument for more information parser.beginGroup("Required I/O parameters"); parser.addArgument( "inputs", "i", mitkCommandLineParser::StringList, "Input files", "Pathes to the input images that should be fused", us::Any(), false, false, false, mitkCommandLineParser::Input); parser.addArgument("output", "o", mitkCommandLineParser::File, "Output file path", "Path to the fused 3D+t image.", us::Any(), false, false, false, mitkCommandLineParser::Output); parser.endGroup(); parser.beginGroup("Optional parameters"); parser.addArgument( "time", "t", mitkCommandLineParser::StringList, "Time bounds", "Defines the time geometry of the resulting dynamic image in [ms]. The first number is the start time point of the first time step. All other numbers are the max bound of a time step. So the structure is [minBound0 maxBound1 [maxBound2 [... maxBoundN]]]; e.g. \"2 3.5 10\" encodes a time geometry with two time steps and that starts at 2 ms and the second time step starts at 3.5 ms and ends at 10 ms. If not set e propertional time geometry with 1 ms duration will be generated!", us::Any(), true, false, false, mitkCommandLineParser::Input); parser.addArgument("help", "h", mitkCommandLineParser::Bool, "Help:", "Show this help text"); parser.endGroup(); //! [add arguments] } bool configureApplicationSettings(std::map parsedArgs) { if (parsedArgs.size() == 0) return false; inFilenames = us::any_cast(parsedArgs["inputs"]); outFileName = us::any_cast(parsedArgs["output"]); if (parsedArgs.count("time")) { auto timeBoundsStr = us::any_cast(parsedArgs["time"]); for (const auto& timeBoundStr : timeBoundsStr) { std::istringstream stream; stream.imbue(std::locale("C")); stream.str(timeBoundStr); mitk::TimePointType time = 0 ; stream >> time; timebounds.emplace_back(time); } } return true; } int main(int argc, char* argv[]) { mitkCommandLineParser parser; setupParser(parser); - mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (classic config)" }, { "MITK DICOM Reader" }); + mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (autoselect)" }, { "" }); const std::map& parsedArgs = parser.parseArguments(argc, argv); if (!configureApplicationSettings(parsedArgs)) { return EXIT_FAILURE; }; // Show a help message if (parsedArgs.count("help") || parsedArgs.count("h")) { std::cout << parser.helpText(); return EXIT_SUCCESS; } if (timebounds.empty()) { timebounds.resize(inFilenames.size()+1); std::iota(timebounds.begin(), timebounds.end(), 0.0); } else if (inFilenames.size() + 1 != timebounds.size()) { std::cerr << "Cannot fuse images. Explicitly specified time bounds do not match. Use --help for more information on how to specify time bounds correctly."; return EXIT_FAILURE; }; //! [do processing] try { std::cout << "Load images:" << std::endl; auto filter = mitk::TemporalJoinImagesFilter::New(); unsigned int step = 0; for (auto path : inFilenames) { std::cout << "Time step #"<(path, &readerFilterFunctor); images.push_back(image); filter->SetInput(step, image); ++step; } filter->SetFirstMinTimeBound(timebounds[0]); filter->SetMaxTimeBounds({ timebounds.begin() + 1, timebounds.end() }); std::cout << "Fuse the images ..." << std::endl; filter->Update(); auto output = filter->GetOutput(); std::cout << "Save output image: " << outFileName << std::endl; mitk::IOUtil::Save(output, outFileName); std::cout << "Processing finished." << std::endl; return EXIT_SUCCESS; } catch (const std::exception& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (...) { MITK_ERROR << "Unexpected error encountered."; return EXIT_FAILURE; } } diff --git a/Modules/ModelFit/cmdapps/GenericFittingMiniApp.cpp b/Modules/ModelFit/cmdapps/GenericFittingMiniApp.cpp index 68984e081d..0e45f362ed 100644 --- a/Modules/ModelFit/cmdapps/GenericFittingMiniApp.cpp +++ b/Modules/ModelFit/cmdapps/GenericFittingMiniApp.cpp @@ -1,360 +1,360 @@ /*============================================================================ The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center (DKFZ) All rights reserved. Use of this source code is governed by a 3-clause BSD license that can be found in the LICENSE file. ============================================================================*/ // std includes #include // itk includes #include "itksys/SystemTools.hxx" // CTK includes #include "mitkCommandLineParser.h" // MITK includes #include #include #include #include #include #include #include #include #include #include #include #include std::string inFilename; std::string outFileName; std::string maskFileName; bool verbose(false); bool roibased(false); std::string functionName; std::string formular; mitk::Image::Pointer image; mitk::Image::Pointer mask; void onFitEvent(::itk::Object* caller, const itk::EventObject & event, void* /*data*/) { itk::ProgressEvent progressEvent; if (progressEvent.CheckEvent(&event)) { mitk::ParameterFitImageGeneratorBase* castedReporter = dynamic_cast(caller); std::cout <GetProgress()*100 << "% "; } } void setupParser(mitkCommandLineParser& parser) { // set general information about your MiniApp parser.setCategory("Dynamic Data Analysis Tools"); parser.setTitle("Generic Fitting"); parser.setDescription("MiniApp that allows to make a pixel based fitting on the intensity signal over time for a given model function."); parser.setContributor("DKFZ MIC"); //! [create parser] //! [add arguments] // how should arguments be prefixed parser.setArgumentPrefix("--", "-"); // add each argument, unless specified otherwise each argument is optional // see mitkCommandLineParser::addArgument for more information parser.beginGroup("Model parameters"); parser.addArgument( "function", "f", mitkCommandLineParser::String, "Model function", "Function that should be used to fit the intensity signals. Options are: \"Linear\" or \"\" (for generic formulas).", us::Any(std::string("Linear"))); parser.addArgument( "formular", "y", mitkCommandLineParser::String, "Generic model function formular", "Formular of a generic model (if selected) that will be parsed and fitted.", us::Any()); parser.endGroup(); parser.beginGroup("Required I/O parameters"); parser.addArgument( "input", "i", mitkCommandLineParser::File, "Input file", "input 3D+t image file", us::Any(), false, false, false, mitkCommandLineParser::Input); parser.addArgument("output", "o", mitkCommandLineParser::File, "Output file template", "where to save the output parameter images. The specified path will be used as template to determine the format (via extension) and the name \"root\". For each parameter a suffix will be added to the name.", us::Any(), false, false, false, mitkCommandLineParser::Output); parser.endGroup(); parser.beginGroup("Optional parameters"); parser.addArgument( "mask", "m", mitkCommandLineParser::File, "Mask file", "Mask that defines the spatial image region that should be fitted. Must have the same geometry as the input image!", us::Any(), true, false, false, mitkCommandLineParser::Input); parser.addArgument( "verbose", "v", mitkCommandLineParser::Bool, "Verbose Output", "Whether to produce verbose output"); parser.addArgument( "roibased", "r", mitkCommandLineParser::Bool, "Roi based fitting", "Will compute a mean intesity signal over the ROI before fitting it. If this mode is used a mask must be specified."); parser.addArgument("help", "h", mitkCommandLineParser::Bool, "Help:", "Show this help text"); parser.endGroup(); //! [add arguments] } bool configureApplicationSettings(std::map parsedArgs) { if (parsedArgs.size() == 0) return false; // parse, cast and set required arguments functionName = "Linear"; if (parsedArgs.count("function")) { functionName = us::any_cast(parsedArgs["function"]); } if (parsedArgs.count("formular")) { formular = us::any_cast(parsedArgs["formular"]); } inFilename = us::any_cast(parsedArgs["input"]); outFileName = us::any_cast(parsedArgs["output"]); verbose = false; if (parsedArgs.count("verbose")) { verbose = us::any_cast(parsedArgs["verbose"]); } roibased = false; if (parsedArgs.count("roibased")) { roibased = us::any_cast(parsedArgs["roibased"]); } if (parsedArgs.count("mask")) { maskFileName = us::any_cast(parsedArgs["mask"]); } return true; } void configureInitialParametersOfParameterizer(mitk::ModelParameterizerBase* parameterizer) { mitk::GenericParamModelParameterizer* genericParameterizer = dynamic_cast(parameterizer); if (genericParameterizer) { genericParameterizer->SetFunctionString(formular); } } mitk::ModelFitFunctorBase::Pointer createDefaultFitFunctor( const mitk::ModelParameterizerBase* parameterizer) { mitk::LevenbergMarquardtModelFitFunctor::Pointer fitFunctor = mitk::LevenbergMarquardtModelFitFunctor::New(); mitk::NormalizedSumOfSquaredDifferencesFitCostFunction::Pointer chi2 = mitk::NormalizedSumOfSquaredDifferencesFitCostFunction::New(); fitFunctor->RegisterEvaluationParameter("Chi^2", chi2); mitk::ModelBase::Pointer refModel = parameterizer->GenerateParameterizedModel(); ::itk::LevenbergMarquardtOptimizer::ScalesType scales; scales.SetSize(refModel->GetNumberOfParameters()); scales.Fill(1.0); fitFunctor->SetScales(scales); fitFunctor->SetDebugParameterMaps(true); return fitFunctor.GetPointer(); } template void generateModelFit_PixelBased(mitk::modelFit::ModelFitInfo::Pointer& /*modelFitInfo*/, mitk::ParameterFitImageGeneratorBase::Pointer& generator) { mitk::PixelBasedParameterFitImageGenerator::Pointer fitGenerator = mitk::PixelBasedParameterFitImageGenerator::New(); typename TParameterizer::Pointer modelParameterizer = TParameterizer::New(); configureInitialParametersOfParameterizer(modelParameterizer); //Specify fitting strategy and criterion parameters mitk::ModelFitFunctorBase::Pointer fitFunctor = createDefaultFitFunctor(modelParameterizer); //Parametrize fit generator fitGenerator->SetModelParameterizer(modelParameterizer); fitGenerator->SetMask(mask); fitGenerator->SetDynamicImage(image); fitGenerator->SetFitFunctor(fitFunctor); generator = fitGenerator.GetPointer(); } template void generateModelFit_ROIBased( mitk::modelFit::ModelFitInfo::Pointer& /*modelFitInfo*/, mitk::ParameterFitImageGeneratorBase::Pointer& generator) { mitk::ROIBasedParameterFitImageGenerator::Pointer fitGenerator = mitk::ROIBasedParameterFitImageGenerator::New(); typename TParameterizer::Pointer modelParameterizer = TParameterizer::New(); configureInitialParametersOfParameterizer(modelParameterizer); //Compute ROI signal mitk::MaskedDynamicImageStatisticsGenerator::Pointer signalGenerator = mitk::MaskedDynamicImageStatisticsGenerator::New(); signalGenerator->SetMask(mask); signalGenerator->SetDynamicImage(image); signalGenerator->Generate(); mitk::MaskedDynamicImageStatisticsGenerator::ResultType roiSignal = signalGenerator->GetMean(); //Specify fitting strategy and criterion parameters mitk::ModelFitFunctorBase::Pointer fitFunctor = createDefaultFitFunctor(modelParameterizer); //Parametrize fit generator fitGenerator->SetModelParameterizer(modelParameterizer); fitGenerator->SetMask(mask); fitGenerator->SetFitFunctor(fitFunctor); fitGenerator->SetSignal(roiSignal); fitGenerator->SetTimeGrid(mitk::ExtractTimeGrid(image)); generator = fitGenerator.GetPointer(); } void doFitting() { mitk::ParameterFitImageGeneratorBase::Pointer generator = nullptr; mitk::modelFit::ModelFitInfo::Pointer fitSession = nullptr; ::itk::CStyleCommand::Pointer command = ::itk::CStyleCommand::New(); command->SetCallback(onFitEvent); bool isLinearFactory = functionName == "Linear"; if (isLinearFactory) { std::cout << "Model: linear" << std::endl; if (!roibased) { generateModelFit_PixelBased(fitSession, generator); } else { generateModelFit_ROIBased(fitSession, generator); } } else { std::cout << "Model: generic (2 parameter)" << std::endl; if (!roibased) { generateModelFit_PixelBased(fitSession, generator); } else { generateModelFit_ROIBased(fitSession, generator); } } if (generator.IsNotNull() ) { std::cout << "Started fitting process..." << std::endl; generator->AddObserver(::itk::AnyEvent(), command); generator->Generate(); std::cout << std::endl << "Finished fitting process" << std::endl; mitk::storeModelFitGeneratorResults(outFileName, generator, fitSession); } else { mitkThrow() << "Fitting error! Could not initalize fitting job."; } } int main(int argc, char* argv[]) { mitkCommandLineParser parser; setupParser(parser); - mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (classic config)" }, { "MITK DICOM Reader" }); + mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (autoselect)" }, { "" }); const std::map& parsedArgs = parser.parseArguments(argc, argv); if (!configureApplicationSettings(parsedArgs)) { return EXIT_FAILURE; }; // Show a help message if (parsedArgs.count("help") || parsedArgs.count("h")) { std::cout << parser.helpText(); return EXIT_SUCCESS; } //! [do processing] try { image = mitk::IOUtil::Load(inFilename, &readerFilterFunctor); std::cout << "Input: " << inFilename << std::endl; if (!maskFileName.empty()) { mask = mitk::IOUtil::Load(maskFileName, &readerFilterFunctor); std::cout << "Mask: " << maskFileName << std::endl; } else { std::cout << "Mask: none" << std::endl; } if (roibased && mask.IsNull()) { mitkThrow() << "Error. Cannot fit. Please specify mask if you select roi based fitting."; } std::cout << "Style: "; if (roibased) { std::cout << "ROI based"; } else { std::cout << "pixel based"; } std::cout << std::endl; doFitting(); std::cout << "Processing finished." << std::endl; return EXIT_SUCCESS; } catch (const itk::ExceptionObject& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (const std::exception& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (...) { MITK_ERROR << "Unexpected error encountered."; return EXIT_FAILURE; } } diff --git a/Modules/ModelFit/cmdapps/PixelDumpMiniApp.cpp b/Modules/ModelFit/cmdapps/PixelDumpMiniApp.cpp index 2c50a02d4b..d3323ed319 100644 --- a/Modules/ModelFit/cmdapps/PixelDumpMiniApp.cpp +++ b/Modules/ModelFit/cmdapps/PixelDumpMiniApp.cpp @@ -1,447 +1,447 @@ /*============================================================================ The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center (DKFZ) All rights reserved. Use of this source code is governed by a 3-clause BSD license that can be found in the LICENSE file. ============================================================================*/ // std includes #include // itk includes #include "itksys/SystemTools.hxx" #include "itkImageRegionConstIteratorWithIndex.h" #include "itkCastImageFilter.h" #include "itkExtractImageFilter.h" // CTK includes #include "mitkCommandLineParser.h" // MITK includes #include #include #include #include "mitkImageAccessByItk.h" #include "mitkImageCast.h" mitkCommandLineParser::StringContainerType inFilenames; std::string outFileName; std::string maskFileName; mitkCommandLineParser::StringContainerType captions; using ImageVectorType = std::vector; ImageVectorType images; mitk::Image::Pointer mask; bool verbose(false); typedef itk::Image InternalImageType; typedef std::map InternalImageMapType; InternalImageMapType internalImages; itk::ImageRegion<3> relevantRegion; InternalImageType::PointType relevantOrigin; InternalImageType::SpacingType relevantSpacing; InternalImageType::DirectionType relevantDirection; typedef itk::Index<3> DumpIndexType; typedef std::vector DumpedValuesType; struct DumpIndexCompare { bool operator() (const DumpIndexType& lhs, const DumpIndexType& rhs) const { if (lhs[0] < rhs[0]) { return true; } else if (lhs[0] > rhs[0]) { return false; } if (lhs[1] < rhs[1]) { return true; } else if (lhs[1] > rhs[1]) { return false; } return lhs[2] < rhs[2]; } }; typedef std::map DumpPixelMapType; DumpPixelMapType dumpedPixels; void setupParser(mitkCommandLineParser& parser) { // set general information about your MiniApp parser.setCategory("Generic Analysis Tools"); parser.setTitle("Pixel Dumper"); parser.setDescription("MiniApp that allows to dump the pixel values of all passed files into a csv. The region of dumping can defined by a mask. All images (and mask) must have the same geometrie."); parser.setContributor("DKFZ MIC"); //! [create parser] //! [add arguments] // how should arguments be prefixed parser.setArgumentPrefix("--", "-"); // add each argument, unless specified otherwise each argument is optional // see mitkCommandLineParser::addArgument for more information parser.beginGroup("Required I/O parameters"); parser.addArgument( "inputs", "i", mitkCommandLineParser::StringList, "Input files", "list of the images that should be dumped.", us::Any(), false); parser.addArgument("output", "o", mitkCommandLineParser::File, "Output file", "where to save the csv.", us::Any(), false, false, false, mitkCommandLineParser::Output); parser.endGroup(); parser.beginGroup("Optional parameters"); parser.addArgument( "mask", "m", mitkCommandLineParser::File, "Mask file", "Mask that defines the spatial image region that should be dumped. Must have the same geometry as the input images!", us::Any(), true, false, false, mitkCommandLineParser::Input); parser.addArgument( "captions", "c", mitkCommandLineParser::StringList, "Captions of image columns", "If provided the pixel columns of the csv will be named according to the passed values instead of using the image pathes. Number of images and names must be equal.", us::Any(), false); parser.addArgument("help", "h", mitkCommandLineParser::Bool, "Help:", "Show this help text"); parser.endGroup(); //! [add arguments] } bool configureApplicationSettings(std::map parsedArgs) { if (parsedArgs.size() == 0) return false; // parse, cast and set required arguments inFilenames = us::any_cast(parsedArgs["inputs"]); outFileName = us::any_cast(parsedArgs["output"]); if (parsedArgs.count("mask")) { maskFileName = us::any_cast(parsedArgs["mask"]); } captions = inFilenames; if (parsedArgs.count("captions")) { captions = us::any_cast(parsedArgs["captions"]); } return true; } template < typename TPixel, unsigned int VImageDimension > void ExtractRelevantInformation( const itk::Image< TPixel, VImageDimension > *image) { relevantRegion = image->GetLargestPossibleRegion(); relevantOrigin = image->GetOrigin(); relevantSpacing = image->GetSpacing(); relevantDirection = image->GetDirection(); } template < typename TPixel, unsigned int VImageDimension > void DoInternalImageConversion( const itk::Image< TPixel, VImageDimension > *image, InternalImageType::Pointer& internalImage) { typedef itk::Image< TPixel, VImageDimension > ImageType; //check if image fit to geometry // Make sure that spacing are the same typename ImageType::SpacingType imageSpacing = image->GetSpacing(); typename ImageType::PointType zeroPoint; zeroPoint.Fill(0.0); if ((zeroPoint + imageSpacing).SquaredEuclideanDistanceTo((zeroPoint + relevantSpacing)) > 1e-6) // for the dumper we are not as strict as mitk normally would be (mitk::eps) { mitkThrow() << "Images need to have same spacing! (Image spacing: " << imageSpacing << "; relevant spacing: " << relevantSpacing << ")"; } // Make sure that orientation of mask and image are the same typename ImageType::DirectionType imageDirection = image->GetDirection(); for (unsigned int i = 0; i < imageDirection.RowDimensions; ++i) { for (unsigned int j = 0; j < imageDirection.ColumnDimensions; ++j) { double differenceDirection = imageDirection[i][j] - relevantDirection[i][j]; if (fabs(differenceDirection) > 1e-6) // SD: 1e6 wird hier zum zweiten mal als Magic Number benutzt -> Konstante { // for the dumper we are not as strict as mitk normally would be (mitk::eps) mitkThrow() << "Images need to have same direction! (Image direction: " << imageDirection << "; relevant direction: " << relevantDirection << ")"; } } } // Make sure that origin of mask and image are the same typename ImageType::PointType imageOrigin = image->GetOrigin(); if (imageOrigin.SquaredEuclideanDistanceTo(relevantOrigin) > 1e-6) { // for the dumper we are not as strict as mitk normally would be (mitk::eps) mitkThrow() << "Image need to have same spacing! (Image spacing: " << imageSpacing << "; relevant spacing: " << relevantOrigin << ")"; } typename ImageType::RegionType imageRegion = image->GetLargestPossibleRegion(); if (!imageRegion.IsInside(relevantRegion) && imageRegion != relevantRegion) { mitkThrow() << "Images need to have same region! (Image region: " << imageRegion << "; relevant region: " << relevantRegion << ")"; } //convert to internal image typedef itk::ExtractImageFilter ExtractFilterType; typename ExtractFilterType::Pointer extractFilter = ExtractFilterType::New(); typedef itk::CastImageFilter CastFilterType; typename CastFilterType::Pointer castFilter = CastFilterType::New(); extractFilter->SetInput(image); extractFilter->SetExtractionRegion(relevantRegion); castFilter->SetInput(extractFilter->GetOutput()); castFilter->Update(); internalImage = castFilter->GetOutput(); } template < typename TPixel, unsigned int VImageDimension > void DoMaskedCollecting( const itk::Image< TPixel, VImageDimension > *image) { typedef itk::Image< TPixel, VImageDimension > ImageType; itk::ImageRegionConstIteratorWithIndex it(image, relevantRegion); it.GoToBegin(); while (!it.IsAtEnd()) { if (mask.IsNull() || it.Get() > 0) { DumpedValuesType values; const auto index = it.GetIndex(); for (auto& imagePos : internalImages) { double value = imagePos.second->GetPixel(index); values.push_back(value); } dumpedPixels.insert(std::make_pair(index, values)); } ++it; } } InternalImageMapType ConvertImageTimeSteps(mitk::Image* image) { InternalImageMapType map; InternalImageType::Pointer internalImage; for (unsigned int i = 0; i < image->GetTimeSteps(); ++i) { mitk::ImageTimeSelector::Pointer imageTimeSelector = mitk::ImageTimeSelector::New(); imageTimeSelector->SetInput(image); imageTimeSelector->SetTimeNr(i); imageTimeSelector->UpdateLargestPossibleRegion(); mitk::Image::Pointer imageTimePoint = imageTimeSelector->GetOutput(); AccessFixedDimensionByItk_1(imageTimePoint, DoInternalImageConversion, 3, internalImage); std::stringstream stream; stream << "[" << i << "]"; map.insert(std::make_pair(stream.str(), internalImage)); } return map; } void doDumping() { if (mask.IsNotNull() && mask->GetTimeSteps() > 1) { std::cout << "Pixel Dumper: Selected mask has multiple timesteps. Only use first timestep to mask the pixel dumping." << std::endl; mitk::ImageTimeSelector::Pointer maskTimeSelector = mitk::ImageTimeSelector::New(); maskTimeSelector->SetInput(mask); maskTimeSelector->SetTimeNr(0); maskTimeSelector->UpdateLargestPossibleRegion(); mask = maskTimeSelector->GetOutput(); } try { if (mask.IsNotNull()) { // if mask exist, we use the mask because it could be a sub region. AccessFixedDimensionByItk(mask, ExtractRelevantInformation, 3); } else { AccessFixedDimensionByItk(images.front(), ExtractRelevantInformation, 3); } } catch (const std::exception& e) { std::cerr << "Error extracting image geometry. Error text: " << e.what(); throw; } for (unsigned int index = 0; index < images.size(); ++index) { try { InternalImageMapType conversionMap = ConvertImageTimeSteps(images[index]); if (conversionMap.size() == 1) { internalImages.insert(std::make_pair(captions[index], conversionMap.begin()->second)); } else if (conversionMap.size() > 1) { for (auto& pos : conversionMap) { std::stringstream namestream; namestream << captions[index] << " " << pos.first; internalImages.insert(std::make_pair(namestream.str(), pos.second)); } } } catch (const std::exception& e) { std::stringstream errorStr; errorStr << "Inconsistent image \"" << captions[index] << "\" will be excluded from the collection. Error: " << e.what(); std::cerr << errorStr.str() << std::endl; } } if (mask.IsNotNull()) { // if mask exist, we use the mask because it could be a sub region. AccessFixedDimensionByItk(mask, DoMaskedCollecting, 3); } else { AccessFixedDimensionByItk(images.front(), DoMaskedCollecting, 3); } } void storeCSV() { std::ofstream resultfile; resultfile.open(outFileName.c_str()); resultfile << "x,y,z"; for (auto aImage : internalImages) { resultfile << "," << aImage.first; } resultfile << std::endl; for (auto dumpPos : dumpedPixels) { resultfile << dumpPos.first[0] << "," << dumpPos.first[1] << "," << dumpPos.first[2]; for(auto d : dumpPos.second) { resultfile << "," << d; } resultfile << std::endl; } } int main(int argc, char* argv[]) { mitkCommandLineParser parser; setupParser(parser); const std::map& parsedArgs = parser.parseArguments(argc, argv); - mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (classic config)" }, { "MITK DICOM Reader" }); + mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (autoselect)" }, { "" }); if (!configureApplicationSettings(parsedArgs)) { return EXIT_FAILURE; }; // Show a help message if (parsedArgs.count("help") || parsedArgs.count("h")) { std::cout << parser.helpText(); return EXIT_SUCCESS; } if (!captions.empty() && inFilenames.size() != captions.size()) { std::cerr << "Cannot dump images. Number of given captions does not equal number of given images."; return EXIT_FAILURE; }; //! [do processing] try { std::cout << "Load images:" << std::endl; for (auto path : inFilenames) { std::cout << "Input: " << path << std::endl; auto image = mitk::IOUtil::Load(path, &readerFilterFunctor); images.push_back(image); } if (!maskFileName.empty()) { mask = mitk::IOUtil::Load(maskFileName, &readerFilterFunctor); std::cout << "Mask: " << maskFileName << std::endl; } else { std::cout << "Mask: none" << std::endl; } doDumping(); storeCSV(); std::cout << "Processing finished." << std::endl; return EXIT_SUCCESS; } catch (const itk::ExceptionObject& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (const std::exception& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (...) { MITK_ERROR << "Unexpected error encountered."; return EXIT_FAILURE; } } diff --git a/Modules/Pharmacokinetics/cmdapps/CurveDescriptorMiniApp.cpp b/Modules/Pharmacokinetics/cmdapps/CurveDescriptorMiniApp.cpp index dd52eec7f8..df8257534f 100644 --- a/Modules/Pharmacokinetics/cmdapps/CurveDescriptorMiniApp.cpp +++ b/Modules/Pharmacokinetics/cmdapps/CurveDescriptorMiniApp.cpp @@ -1,242 +1,242 @@ /*============================================================================ The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center (DKFZ) All rights reserved. Use of this source code is governed by a 3-clause BSD license that can be found in the LICENSE file. ============================================================================*/ // std includes #include // itk includes #include "itksys/SystemTools.hxx" // CTK includes #include "mitkCommandLineParser.h" // MITK includes #include #include #include #include #include #include #include #include #include std::string inFilename; std::string outFileName; std::string maskFileName; bool verbose(false); bool preview(false); mitk::Image::Pointer image; mitk::Image::Pointer mask; void onFitEvent(::itk::Object* caller, const itk::EventObject & event, void* /*data*/) { itk::ProgressEvent progressEvent; if (progressEvent.CheckEvent(&event)) { mitk::PixelBasedDescriptionParameterImageGenerator* castedReporter = dynamic_cast(caller); std::cout <GetProgress()*100 << "% "; } } void setupParser(mitkCommandLineParser& parser) { // set general information about your MiniApp parser.setCategory("Dynamic Data Analysis Tools"); parser.setTitle("Curve Descriptor"); parser.setDescription("MiniApp that allows to generate curve descriptor maps for dynamic image."); parser.setContributor("DKFZ MIC"); //! [create parser] //! [add arguments] // how should arguments be prefixed parser.setArgumentPrefix("--", "-"); // add each argument, unless specified otherwise each argument is optional // see mitkCommandLineParser::addArgument for more information parser.beginGroup("Required I/O parameters"); parser.addArgument( "input", "i", mitkCommandLineParser::File, "Input file", "input 3D+t image file", us::Any(), false, false, false, mitkCommandLineParser::Input); parser.addArgument("output", "o", mitkCommandLineParser::File, "Output file template", "where to save the output parameter images. The specified path will be used as template to determine the format (via extension) and the name \"root\". For each parameter a suffix will be added to the name.", us::Any(), false, false, false, mitkCommandLineParser::Output); parser.endGroup(); parser.beginGroup("Optional parameters"); parser.addArgument( "mask", "m", mitkCommandLineParser::File, "Mask file", "Mask that defines the spatial image region that should be fitted. Must have the same geometry as the input image!", us::Any(), true, false, false, mitkCommandLineParser::Input); parser.addArgument( "verbose", "v", mitkCommandLineParser::Bool, "Verbose Output", "Whether to produce verbose output"); parser.addArgument( "preview", "p", mitkCommandLineParser::Bool, "Preview outputs", "The application previews the outputs (filename, type) it would produce with the current settings."); parser.addArgument("help", "h", mitkCommandLineParser::Bool, "Help:", "Show this help text"); parser.endGroup(); //! [add arguments] } bool configureApplicationSettings(std::map parsedArgs) { if (parsedArgs.size() == 0) return false; verbose = false; if (parsedArgs.count("verbose")) { verbose = us::any_cast(parsedArgs["verbose"]); } if (parsedArgs.count("mask")) { maskFileName = us::any_cast(parsedArgs["mask"]); } preview = false; if (parsedArgs.count("preview")) { preview = us::any_cast(parsedArgs["preview"]); } inFilename = us::any_cast(parsedArgs["input"]); outFileName = us::any_cast(parsedArgs["output"]); return true; } void ConfigureFunctor(mitk::CurveParameterFunctor* functor) { mitk::CurveDescriptionParameterBase::Pointer parameterFunction = mitk::AreaUnderTheCurveDescriptionParameter::New().GetPointer(); functor->RegisterDescriptionParameter("AUC", parameterFunction); parameterFunction = mitk::AreaUnderFirstMomentDescriptionParameter::New().GetPointer(); functor->RegisterDescriptionParameter("AUMC", parameterFunction); parameterFunction = mitk::MeanResidenceTimeDescriptionParameter::New().GetPointer(); functor->RegisterDescriptionParameter("MRT", parameterFunction); parameterFunction = mitk::TimeToPeakCurveDescriptionParameter::New().GetPointer(); functor->RegisterDescriptionParameter("TimeToPeak", parameterFunction); }; void doDescription() { mitk::PixelBasedDescriptionParameterImageGenerator::Pointer generator = mitk::PixelBasedDescriptionParameterImageGenerator::New(); mitk::CurveParameterFunctor::Pointer functor = mitk::CurveParameterFunctor::New(); ConfigureFunctor(functor); functor->SetGrid(mitk::ExtractTimeGrid(image)); generator->SetFunctor(functor); generator->SetDynamicImage(image); generator->SetMask(mask); ::itk::CStyleCommand::Pointer command = ::itk::CStyleCommand::New(); command->SetCallback(onFitEvent); std::cout << "Started curve descriptor computation process..." << std::endl; generator->AddObserver(::itk::AnyEvent(), command); generator->Generate(); std::cout << std::endl << "Finished computation process" << std::endl; for (auto imageIterator : generator->GetParameterImages()) { mitk::storeParameterResultImage(outFileName, imageIterator.first, imageIterator.second); } } void doPreview() { mitk::CurveParameterFunctor::Pointer functor = mitk::CurveParameterFunctor::New(); ConfigureFunctor(functor); auto pNames = functor->GetDescriptionParameterNames(); for (auto aName : pNames) { auto fullPath = mitk::generateModelFitResultImagePath(outFileName, aName); std::cout << "Store result parameter: " << aName << " -> " << fullPath << std::endl; } } int main(int argc, char* argv[]) { mitkCommandLineParser parser; setupParser(parser); - mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (classic config)" }, { "MITK DICOM Reader" }); + mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (autoselect)" }, { "" }); const std::map& parsedArgs = parser.parseArguments(argc, argv); if (!configureApplicationSettings(parsedArgs)) { return EXIT_FAILURE; }; // Show a help message if (parsedArgs.count("help") || parsedArgs.count("h")) { std::cout << parser.helpText(); return EXIT_SUCCESS; } //! [do processing] try { if (preview) { doPreview(); } else { image = mitk::IOUtil::Load(inFilename, &readerFilterFunctor); std::cout << "Input: " << inFilename << std::endl; if (!maskFileName.empty()) { mask = mitk::IOUtil::Load(maskFileName, &readerFilterFunctor); std::cout << "Mask: " << maskFileName << std::endl; } else { std::cout << "Mask: none" << std::endl; } doDescription(); } std::cout << "Processing finished." << std::endl; return EXIT_SUCCESS; } catch (const itk::ExceptionObject& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (const std::exception& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (...) { MITK_ERROR << "Unexpected error encountered."; return EXIT_FAILURE; } } diff --git a/Modules/Pharmacokinetics/cmdapps/MRPerfusionMiniApp.cpp b/Modules/Pharmacokinetics/cmdapps/MRPerfusionMiniApp.cpp index 9fc08615b9..d871108746 100644 --- a/Modules/Pharmacokinetics/cmdapps/MRPerfusionMiniApp.cpp +++ b/Modules/Pharmacokinetics/cmdapps/MRPerfusionMiniApp.cpp @@ -1,890 +1,890 @@ /*============================================================================ The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center (DKFZ) All rights reserved. Use of this source code is governed by a 3-clause BSD license that can be found in the LICENSE file. ============================================================================*/ // std includes #include // itk includes #include "itksys/SystemTools.hxx" // CTK includes #include "mitkCommandLineParser.h" // MITK includes #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include std::string inFilename; std::string outFileName; std::string maskFileName; std::string aifMaskFileName; std::string aifImageFileName; mitk::Image::Pointer image; mitk::Image::Pointer mask; mitk::Image::Pointer aifImage; mitk::Image::Pointer aifMask; bool useConstraints(false); bool verbose(false); bool roibased(false); bool preview(false); std::string modelName; float aifHematocritLevel(0); float brixInjectionTime(0); const std::string MODEL_NAME_2SL = "2SL"; const std::string MODEL_NAME_3SL = "3SL"; const std::string MODEL_NAME_descriptive = "descriptive"; const std::string MODEL_NAME_tofts = "tofts"; const std::string MODEL_NAME_2CX = "2CX"; void onFitEvent(::itk::Object* caller, const itk::EventObject & event, void* /*data*/) { itk::ProgressEvent progressEvent; if (progressEvent.CheckEvent(&event)) { mitk::ParameterFitImageGeneratorBase* castedReporter = dynamic_cast(caller); std::cout <GetProgress()*100 << "% "; } } void setupParser(mitkCommandLineParser& parser) { // set general information about your MiniApp parser.setCategory("Dynamic Data Analysis Tools"); parser.setTitle("MR Perfusion"); parser.setDescription("MiniApp that allows to fit MRI perfusion models and generates the according parameter maps. IMPORTANT!!!: The app assumes that the input images (signal and AIF) are concentration images. If your images do not hold this assumption, convert the image date before using this app (e.g. by using the signal-to-concentration-converter mini app."); parser.setContributor("DKFZ MIC"); //! [create parser] //! [add arguments] // how should arguments be prefixed parser.setArgumentPrefix("--", "-"); // add each argument, unless specified otherwise each argument is optional // see mitkCommandLineParser::addArgument for more information parser.beginGroup("Model parameters"); parser.addArgument( "model", "l", mitkCommandLineParser::String, "Model function", "Model that should be used to fit the concentration signal. Options are: \""+MODEL_NAME_descriptive+"\" (descriptive pharmacokinetic Brix model),\"" + MODEL_NAME_2SL + "\" (two step linear model),\""+MODEL_NAME_3SL+"\" (three step linear model), \""+MODEL_NAME_tofts+"\" (extended tofts model) or \""+MODEL_NAME_2CX+"\" (two compartment exchange model).", us::Any(std::string(MODEL_NAME_tofts))); parser.addArgument( "injectiontime", "j", mitkCommandLineParser::Float, "Injection time [min]", "Injection time of the bolus. This information is needed for the descriptive pharmacokinetic Brix model.", us::Any()); parser.endGroup(); parser.beginGroup("Required I/O parameters"); parser.addArgument( "input", "i", mitkCommandLineParser::File, "Input file", "input 3D+t image file", us::Any(), false, false, false, mitkCommandLineParser::Input); parser.addArgument("output", "o", mitkCommandLineParser::File, "Output file template", "where to save the output parameter images. The specified path will be used as template to determine the format (via extension) and the name \"root\". For each parameter a suffix will be added to the name.", us::Any(), false, false, false, mitkCommandLineParser::Output); parser.endGroup(); parser.beginGroup("AIF parameters"); parser.addArgument( "aifmask", "n", mitkCommandLineParser::File, "AIF mask file", "Mask that defines the spatial image region that should be used as AIF for models that need one. Must have the same geometry as the AIF input image!", us::Any(), true, false, false, mitkCommandLineParser::Input); parser.addArgument( "aifimage", "a", mitkCommandLineParser::File, "AIF image file", "3D+t image that defines the image that containes the AIF signal. If this flag is not set and the model needs a AIF, the CLI will assume that the AIF is encoded in the normal image. Must have the same geometry as the AIF mask!", us::Any(), true, false, false, mitkCommandLineParser::Input); parser.addArgument( "hematocrit", "h", mitkCommandLineParser::Float, "Hematocrit Level", "Value needed for correct AIF computation. Only needed if model needs an AIF. Default value is 0.45.", us::Any(0.45)); parser.endGroup(); parser.beginGroup("Optional parameters"); parser.addArgument( "mask", "m", mitkCommandLineParser::File, "Mask file", "Mask that defines the spatial image region that should be fitted. Must have the same geometry as the input image!", us::Any(), true, false, false, mitkCommandLineParser::Input); parser.addArgument( "verbose", "v", mitkCommandLineParser::Bool, "Verbose Output", "Whether to produce verbose output"); parser.addArgument( "roibased", "r", mitkCommandLineParser::Bool, "Roi based fitting", "Will compute a mean intesity signal over the ROI before fitting it. If this mode is used a mask must be specified."); parser.addArgument( "constraints", "c", mitkCommandLineParser::Bool, "Constraints", "Indicates if constraints should be used for the fitting (if flag is set the default contraints will be used.).", us::Any(false)); parser.addArgument( "preview", "p", mitkCommandLineParser::Bool, "Preview outputs", "The application previews the outputs (filename, type) it would produce with the current settings."); parser.addArgument("help", "h", mitkCommandLineParser::Bool, "Help:", "Show this help text"); parser.endGroup(); //! [add arguments] } bool configureApplicationSettings(std::map parsedArgs) { if (parsedArgs.size() == 0) return false; // parse, cast and set required arguments modelName = MODEL_NAME_tofts; if (parsedArgs.count("model")) { modelName = us::any_cast(parsedArgs["model"]); } inFilename = us::any_cast(parsedArgs["input"]); outFileName = us::any_cast(parsedArgs["output"]); if (parsedArgs.count("mask")) { maskFileName = us::any_cast(parsedArgs["mask"]); } if (parsedArgs.count("aifimage")) { aifImageFileName = us::any_cast(parsedArgs["aifimage"]); } if (parsedArgs.count("aifmask")) { aifMaskFileName = us::any_cast(parsedArgs["aifmask"]); } verbose = false; if (parsedArgs.count("verbose")) { verbose = us::any_cast(parsedArgs["verbose"]); } preview = false; if (parsedArgs.count("preview")) { preview = us::any_cast(parsedArgs["preview"]); } roibased = false; if (parsedArgs.count("roibased")) { roibased = us::any_cast(parsedArgs["roibased"]); } useConstraints = false; if (parsedArgs.count("constraints")) { useConstraints = us::any_cast(parsedArgs["constraints"]); } aifHematocritLevel = 0.45; if (parsedArgs.count("hematocrit")) { aifHematocritLevel = us::any_cast(parsedArgs["hematocrit"]); } brixInjectionTime = 0.0; if (parsedArgs.count("injectiontime")) { brixInjectionTime = us::any_cast(parsedArgs["injectiontime"]); } return true; } mitk::ModelFitFunctorBase::Pointer createDefaultFitFunctor( const mitk::ModelParameterizerBase* parameterizer, const mitk::ModelFactoryBase* modelFactory) { mitk::LevenbergMarquardtModelFitFunctor::Pointer fitFunctor = mitk::LevenbergMarquardtModelFitFunctor::New(); mitk::NormalizedSumOfSquaredDifferencesFitCostFunction::Pointer chi2 = mitk::NormalizedSumOfSquaredDifferencesFitCostFunction::New(); fitFunctor->RegisterEvaluationParameter("Chi^2", chi2); if (useConstraints) { fitFunctor->SetConstraintChecker(modelFactory->CreateDefaultConstraints().GetPointer()); } mitk::ModelBase::Pointer refModel = parameterizer->GenerateParameterizedModel(); ::itk::LevenbergMarquardtOptimizer::ScalesType scales; scales.SetSize(refModel->GetNumberOfParameters()); scales.Fill(1.0); fitFunctor->SetScales(scales); fitFunctor->SetDebugParameterMaps(true); return fitFunctor.GetPointer(); } /**Helper that ensures that the mask (if it exists) is always 3D image. If the mask is originally an 4D image, the first time step will be used.*/ mitk::Image::Pointer getMask3D() { mitk::Image::Pointer result; if (mask.IsNotNull()) { result = mask; //mask settings if (mask->GetTimeSteps() > 1) { MITK_INFO << "Selected mask has multiple timesteps. Only use first timestep to mask model fit."; mitk::ImageTimeSelector::Pointer maskedImageTimeSelector = mitk::ImageTimeSelector::New(); maskedImageTimeSelector->SetInput(mask); maskedImageTimeSelector->SetTimeNr(0); maskedImageTimeSelector->UpdateLargestPossibleRegion(); result = maskedImageTimeSelector->GetOutput(); } } return result; } void getAIF(mitk::AIFBasedModelBase::AterialInputFunctionType& aif, mitk::AIFBasedModelBase::AterialInputFunctionType& aifTimeGrid) { if (aifMask.IsNotNull()) { aif.clear(); aifTimeGrid.clear(); mitk::AterialInputFunctionGenerator::Pointer aifGenerator = mitk::AterialInputFunctionGenerator::New(); //Hematocrit level aifGenerator->SetHCL(aifHematocritLevel); std::cout << "AIF hematocrit level: " << aifHematocritLevel << std::endl; mitk::Image::Pointer selectedAIFMask = aifMask; //mask settings if (aifMask->GetTimeSteps() > 1) { MITK_INFO << "Selected AIF mask has multiple timesteps. Only use first timestep to mask model fit."; mitk::ImageTimeSelector::Pointer maskedImageTimeSelector = mitk::ImageTimeSelector::New(); maskedImageTimeSelector->SetInput(aifMask); maskedImageTimeSelector->SetTimeNr(0); maskedImageTimeSelector->UpdateLargestPossibleRegion(); aifMask = maskedImageTimeSelector->GetOutput(); } aifGenerator->SetMask(aifMask); mitk::Image::Pointer selectedAIFImage = image; //image settings if (aifImage.IsNotNull()) { selectedAIFImage = aifImage; } aifGenerator->SetDynamicImage(selectedAIFImage); aif = aifGenerator->GetAterialInputFunction(); aifTimeGrid = aifGenerator->GetAterialInputFunctionTimeGrid(); } else { mitkThrow() << "Cannot generate AIF. AIF mask was not specified or correctly loaded."; } } void generateDescriptiveBrixModel_PixelBased(mitk::modelFit::ModelFitInfo::Pointer& modelFitInfo, mitk::ParameterFitImageGeneratorBase::Pointer& generator) { mitk::PixelBasedParameterFitImageGenerator::Pointer fitGenerator = mitk::PixelBasedParameterFitImageGenerator::New(); mitk::DescriptivePharmacokineticBrixModelParameterizer::Pointer modelParameterizer = mitk::DescriptivePharmacokineticBrixModelParameterizer::New(); mitk::Image::Pointer mask3D = getMask3D(); //Model configuration (static parameters) can be done now modelParameterizer->SetTau(brixInjectionTime); std::cout << "Injection time [min]: " << brixInjectionTime << std::endl; mitk::ImageTimeSelector::Pointer imageTimeSelector = mitk::ImageTimeSelector::New(); imageTimeSelector->SetInput(image); imageTimeSelector->SetTimeNr(0); imageTimeSelector->UpdateLargestPossibleRegion(); mitk::DescriptivePharmacokineticBrixModelParameterizer::BaseImageType::Pointer baseImage; mitk::CastToItkImage(imageTimeSelector->GetOutput(), baseImage); modelParameterizer->SetBaseImage(baseImage); //Specify fitting strategy and criterion parameters mitk::ModelFactoryBase::Pointer factory = mitk::DescriptivePharmacokineticBrixModelFactory::New().GetPointer(); mitk::ModelFitFunctorBase::Pointer fitFunctor = createDefaultFitFunctor(modelParameterizer, factory); //Parametrize fit generator fitGenerator->SetModelParameterizer(modelParameterizer); std::string roiUID = ""; if (mask3D.IsNotNull()) { fitGenerator->SetMask(mask3D); roiUID = mask->GetUID(); } fitGenerator->SetDynamicImage(image); fitGenerator->SetFitFunctor(fitFunctor); generator = fitGenerator.GetPointer(); //Create model info modelFitInfo = mitk::modelFit::CreateFitInfoFromModelParameterizer(modelParameterizer, image, mitk::ModelFitConstants::FIT_TYPE_VALUE_PIXELBASED(), roiUID); } void generateDescriptiveBrixModel_ROIBased(mitk::modelFit::ModelFitInfo::Pointer& modelFitInfo, mitk::ParameterFitImageGeneratorBase::Pointer& generator) { mitk::Image::Pointer mask3D = getMask3D(); if (mask3D.IsNull()) { return; } mitk::ROIBasedParameterFitImageGenerator::Pointer fitGenerator = mitk::ROIBasedParameterFitImageGenerator::New(); mitk::DescriptivePharmacokineticBrixModelValueBasedParameterizer::Pointer modelParameterizer = mitk::DescriptivePharmacokineticBrixModelValueBasedParameterizer::New(); //Compute ROI signal mitk::MaskedDynamicImageStatisticsGenerator::Pointer signalGenerator = mitk::MaskedDynamicImageStatisticsGenerator::New(); signalGenerator->SetMask(mask3D); signalGenerator->SetDynamicImage(image); signalGenerator->Generate(); mitk::MaskedDynamicImageStatisticsGenerator::ResultType roiSignal = signalGenerator->GetMean(); //Model configuration (static parameters) can be done now modelParameterizer->SetTau(brixInjectionTime); std::cout << "Injection time [min]: " << brixInjectionTime << std::endl; modelParameterizer->SetBaseValue(roiSignal[0]); //Specify fitting strategy and criterion parameters mitk::ModelFactoryBase::Pointer factory = mitk::DescriptivePharmacokineticBrixModelFactory::New().GetPointer(); mitk::ModelFitFunctorBase::Pointer fitFunctor = createDefaultFitFunctor(modelParameterizer, factory); //Parametrize fit generator fitGenerator->SetModelParameterizer(modelParameterizer); fitGenerator->SetMask(mask3D); fitGenerator->SetFitFunctor(fitFunctor); fitGenerator->SetSignal(roiSignal); fitGenerator->SetTimeGrid(mitk::ExtractTimeGrid(image)); generator = fitGenerator.GetPointer(); std::string roiUID = mask->GetUID(); //Create model info modelFitInfo = mitk::modelFit::CreateFitInfoFromModelParameterizer(modelParameterizer, image, mitk::ModelFitConstants::FIT_TYPE_VALUE_ROIBASED(), roiUID); mitk::ScalarListLookupTable::ValueType infoSignal; for (mitk::MaskedDynamicImageStatisticsGenerator::ResultType::const_iterator pos = roiSignal.begin(); pos != roiSignal.end(); ++pos) { infoSignal.push_back(*pos); } modelFitInfo->inputData.SetTableValue("ROI", infoSignal); } template void GenerateLinearModelFit_PixelBased(mitk::modelFit::ModelFitInfo::Pointer& modelFitInfo, mitk::ParameterFitImageGeneratorBase::Pointer& generator) { mitk::PixelBasedParameterFitImageGenerator::Pointer fitGenerator = mitk::PixelBasedParameterFitImageGenerator::New(); typename TParameterizer::Pointer modelParameterizer = TParameterizer::New(); mitk::Image::Pointer mask3D = getMask3D(); //Specify fitting strategy and criterion parameters mitk::ModelFactoryBase::Pointer factory = TFactory::New().GetPointer(); mitk::ModelFitFunctorBase::Pointer fitFunctor = createDefaultFitFunctor(modelParameterizer, factory); //Parametrize fit generator fitGenerator->SetModelParameterizer(modelParameterizer); std::string roiUID = ""; if (mask3D.IsNotNull()) { fitGenerator->SetMask(mask3D); roiUID = mask->GetUID(); } fitGenerator->SetDynamicImage(image); fitGenerator->SetFitFunctor(fitFunctor); generator = fitGenerator.GetPointer(); //Create model info modelFitInfo = mitk::modelFit::CreateFitInfoFromModelParameterizer(modelParameterizer, image, mitk::ModelFitConstants::FIT_TYPE_VALUE_PIXELBASED(), roiUID); } template void GenerateLinearModelFit_ROIBased(mitk::modelFit::ModelFitInfo::Pointer& modelFitInfo, mitk::ParameterFitImageGeneratorBase::Pointer& generator) { mitk::Image::Pointer mask3D = getMask3D(); if (mask3D.IsNull()) { return; } mitk::ROIBasedParameterFitImageGenerator::Pointer fitGenerator = mitk::ROIBasedParameterFitImageGenerator::New(); typename TParameterizer::Pointer modelParameterizer = TParameterizer::New(); //Compute ROI signal mitk::MaskedDynamicImageStatisticsGenerator::Pointer signalGenerator = mitk::MaskedDynamicImageStatisticsGenerator::New(); signalGenerator->SetMask(mask3D); signalGenerator->SetDynamicImage(image); signalGenerator->Generate(); mitk::MaskedDynamicImageStatisticsGenerator::ResultType roiSignal = signalGenerator->GetMean(); //Specify fitting strategy and criterion parameters mitk::ModelFactoryBase::Pointer factory = TFactory::New().GetPointer(); mitk::ModelFitFunctorBase::Pointer fitFunctor = createDefaultFitFunctor(modelParameterizer, factory); //Parametrize fit generator fitGenerator->SetModelParameterizer(modelParameterizer); fitGenerator->SetMask(mask3D); fitGenerator->SetFitFunctor(fitFunctor); fitGenerator->SetSignal(roiSignal); fitGenerator->SetTimeGrid(mitk::ExtractTimeGrid(image)); generator = fitGenerator.GetPointer(); std::string roiUID = mask->GetUID(); //Create model info modelFitInfo = mitk::modelFit::CreateFitInfoFromModelParameterizer(modelParameterizer, image, mitk::ModelFitConstants::FIT_TYPE_VALUE_ROIBASED(), roiUID); mitk::ScalarListLookupTable::ValueType infoSignal; for (mitk::MaskedDynamicImageStatisticsGenerator::ResultType::const_iterator pos = roiSignal.begin(); pos != roiSignal.end(); ++pos) { infoSignal.push_back(*pos); } modelFitInfo->inputData.SetTableValue("ROI", infoSignal); } template void generateAIFbasedModelFit_PixelBased(mitk::modelFit::ModelFitInfo::Pointer& modelFitInfo, mitk::ParameterFitImageGeneratorBase::Pointer& generator) { mitk::PixelBasedParameterFitImageGenerator::Pointer fitGenerator = mitk::PixelBasedParameterFitImageGenerator::New(); typename TParameterizer::Pointer modelParameterizer = TParameterizer::New(); mitk::AIFBasedModelBase::AterialInputFunctionType aif; mitk::AIFBasedModelBase::AterialInputFunctionType aifTimeGrid; getAIF(aif, aifTimeGrid); modelParameterizer->SetAIF(aif); modelParameterizer->SetAIFTimeGrid(aifTimeGrid); mitk::Image::Pointer mask3D = getMask3D(); //Specify fitting strategy and criterion parameters mitk::ModelFactoryBase::Pointer factory = TFactory::New().GetPointer(); mitk::ModelFitFunctorBase::Pointer fitFunctor = createDefaultFitFunctor(modelParameterizer, factory); //Parametrize fit generator fitGenerator->SetModelParameterizer(modelParameterizer); std::string roiUID = ""; if (mask3D.IsNotNull()) { fitGenerator->SetMask(mask3D); roiUID = mask->GetUID(); } fitGenerator->SetDynamicImage(image); fitGenerator->SetFitFunctor(fitFunctor); generator = fitGenerator.GetPointer(); //Create model info modelFitInfo = mitk::modelFit::CreateFitInfoFromModelParameterizer(modelParameterizer, image, mitk::ModelFitConstants::FIT_TYPE_VALUE_PIXELBASED(), roiUID); mitk::ScalarListLookupTable::ValueType infoSignal; for (mitk::AIFBasedModelBase::AterialInputFunctionType::const_iterator pos = aif.begin(); pos != aif.end(); ++pos) { infoSignal.push_back(*pos); } modelFitInfo->inputData.SetTableValue("AIF", infoSignal); } template void generateAIFbasedModelFit_ROIBased( mitk::modelFit::ModelFitInfo::Pointer& modelFitInfo, mitk::ParameterFitImageGeneratorBase::Pointer& generator) { mitk::Image::Pointer mask3D = getMask3D(); if (mask3D.IsNull()) { return; } mitk::ROIBasedParameterFitImageGenerator::Pointer fitGenerator = mitk::ROIBasedParameterFitImageGenerator::New(); typename TParameterizer::Pointer modelParameterizer = TParameterizer::New(); mitk::AIFBasedModelBase::AterialInputFunctionType aif; mitk::AIFBasedModelBase::AterialInputFunctionType aifTimeGrid; getAIF(aif, aifTimeGrid); modelParameterizer->SetAIF(aif); modelParameterizer->SetAIFTimeGrid(aifTimeGrid); //Compute ROI signal mitk::MaskedDynamicImageStatisticsGenerator::Pointer signalGenerator = mitk::MaskedDynamicImageStatisticsGenerator::New(); signalGenerator->SetMask(mask3D); signalGenerator->SetDynamicImage(image); signalGenerator->Generate(); mitk::MaskedDynamicImageStatisticsGenerator::ResultType roiSignal = signalGenerator->GetMean(); //Specify fitting strategy and criterion parameters mitk::ModelFactoryBase::Pointer factory = TFactory::New().GetPointer(); mitk::ModelFitFunctorBase::Pointer fitFunctor = createDefaultFitFunctor(modelParameterizer, factory); //Parametrize fit generator fitGenerator->SetModelParameterizer(modelParameterizer); fitGenerator->SetMask(mask3D); fitGenerator->SetFitFunctor(fitFunctor); fitGenerator->SetSignal(roiSignal); fitGenerator->SetTimeGrid(mitk::ExtractTimeGrid(image)); generator = fitGenerator.GetPointer(); std::string roiUID = mask->GetUID(); //Create model info modelFitInfo = mitk::modelFit::CreateFitInfoFromModelParameterizer(modelParameterizer, image, mitk::ModelFitConstants::FIT_TYPE_VALUE_ROIBASED(), roiUID); mitk::ScalarListLookupTable::ValueType infoSignal; for (mitk::MaskedDynamicImageStatisticsGenerator::ResultType::const_iterator pos = roiSignal.begin(); pos != roiSignal.end(); ++pos) { infoSignal.push_back(*pos); } modelFitInfo->inputData.SetTableValue("ROI", infoSignal); infoSignal.clear(); for (mitk::AIFBasedModelBase::AterialInputFunctionType::const_iterator pos = aif.begin(); pos != aif.end(); ++pos) { infoSignal.push_back(*pos); } modelFitInfo->inputData.SetTableValue("AIF", infoSignal); } void storeResultImage(const std::string& name, mitk::Image* image, mitk::modelFit::Parameter::Type nodeType, const mitk::modelFit::ModelFitInfo* modelFitInfo) { mitk::modelFit::SetModelFitDataProperties(image, name, nodeType, modelFitInfo); std::string ext = ::itksys::SystemTools::GetFilenameLastExtension(outFileName); std::string dir = itksys::SystemTools::GetFilenamePath(outFileName); dir = itksys::SystemTools::ConvertToOutputPath(dir); std::string rootName = itksys::SystemTools::GetFilenameWithoutLastExtension(outFileName); std::string fileName = rootName + "_" + name + ext; std::vector pathElements; pathElements.push_back(dir); pathElements.push_back(fileName); std::string fullOutPath = itksys::SystemTools::ConvertToOutputPath(dir + "/" + fileName); mitk::IOUtil::Save(image, fullOutPath); std::cout << "Store result (parameter: "<(fitSession, generator); } else { GenerateLinearModelFit_ROIBased(fitSession, generator); } } else if (is2SLFactory) { std::cout << "Model: two step linear model" << std::endl; if (!roibased) { GenerateLinearModelFit_PixelBased(fitSession, generator); } else { GenerateLinearModelFit_ROIBased(fitSession, generator); } } else if (isToftsFactory) { std::cout << "Model: extended tofts model" << std::endl; if (!roibased) { generateAIFbasedModelFit_PixelBased(fitSession, generator); } else { generateAIFbasedModelFit_ROIBased(fitSession, generator); } } else if (is2CXMFactory) { std::cout << "Model: two compartment exchange model" << std::endl; if (!roibased) { generateAIFbasedModelFit_PixelBased(fitSession, generator); } else { generateAIFbasedModelFit_ROIBased(fitSession, generator); } } else { std::cerr << "ERROR. Model flag is unknown. Given flag: " << modelName << std::endl; } } void doFitting() { mitk::ParameterFitImageGeneratorBase::Pointer generator = nullptr; mitk::modelFit::ModelFitInfo::Pointer fitSession = nullptr; ::itk::CStyleCommand::Pointer command = ::itk::CStyleCommand::New(); command->SetCallback(onFitEvent); createFitGenerator(fitSession, generator); if (generator.IsNotNull() ) { std::cout << "Started fitting process..." << std::endl; generator->AddObserver(::itk::AnyEvent(), command); generator->Generate(); std::cout << std::endl << "Finished fitting process" << std::endl; mitk::storeModelFitGeneratorResults(outFileName, generator, fitSession); } else { mitkThrow() << "Fitting error! Could not initialize fitting job."; } } void doPreview() { mitk::ParameterFitImageGeneratorBase::Pointer generator = nullptr; mitk::modelFit::ModelFitInfo::Pointer fitSession = nullptr; createFitGenerator(fitSession, generator); if (generator.IsNotNull()) { mitk::previewModelFitGeneratorResults(outFileName, generator); } else { mitkThrow() << "Fitting error! Could not initialize fitting job."; } } int main(int argc, char* argv[]) { mitkCommandLineParser parser; setupParser(parser); const std::map& parsedArgs = parser.parseArguments(argc, argv); - mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (classic config)" }, { "MITK DICOM Reader" }); + mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (autoselect)" }, { "" }); if (!configureApplicationSettings(parsedArgs)) { return EXIT_FAILURE; }; // Show a help message if (parsedArgs.count("help") || parsedArgs.count("h")) { std::cout << parser.helpText(); return EXIT_SUCCESS; } //! [do processing] try { image = mitk::IOUtil::Load(inFilename, &readerFilterFunctor); std::cout << "Input: " << inFilename << std::endl; if (!maskFileName.empty()) { mask = mitk::IOUtil::Load(maskFileName, &readerFilterFunctor); std::cout << "Mask: " << maskFileName << std::endl; } else { std::cout << "Mask: none" << std::endl; } if (modelName != MODEL_NAME_descriptive && modelName != MODEL_NAME_3SL && MODEL_NAME_2SL != modelName) { if (!aifMaskFileName.empty()) { aifMask = mitk::IOUtil::Load(aifMaskFileName, &readerFilterFunctor); std::cout << "AIF mask: " << aifMaskFileName << std::endl; } else { mitkThrow() << "Error. Cannot fit. Choosen model needs an AIF. Please specify AIF mask (--aifmask)."; } if (!aifImageFileName.empty()) { aifImage = mitk::IOUtil::Load(aifImageFileName, &readerFilterFunctor); std::cout << "AIF image: " << aifImageFileName << std::endl; } else { std::cout << "AIF image: none (using signal image)" << std::endl; } } if (roibased && mask.IsNull()) { mitkThrow() << "Error. Cannot fit. Please specify mask if you select roi based fitting."; } std::cout << "Style: "; if (roibased) { std::cout << "ROI based"; } else { std::cout << "pixel based"; } std::cout << std::endl; if (preview) { doPreview(); } else { doFitting(); } std::cout << "Processing finished." << std::endl; return EXIT_SUCCESS; } catch (const itk::ExceptionObject& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (const std::exception& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (...) { MITK_ERROR << "Unexpected error encountered."; return EXIT_FAILURE; } } diff --git a/Modules/Pharmacokinetics/cmdapps/MRSignal2ConcentrationMiniApp.cpp b/Modules/Pharmacokinetics/cmdapps/MRSignal2ConcentrationMiniApp.cpp index bd517b3abb..c9057a5bc8 100644 --- a/Modules/Pharmacokinetics/cmdapps/MRSignal2ConcentrationMiniApp.cpp +++ b/Modules/Pharmacokinetics/cmdapps/MRSignal2ConcentrationMiniApp.cpp @@ -1,287 +1,287 @@ /*============================================================================ The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center (DKFZ) All rights reserved. Use of this source code is governed by a 3-clause BSD license that can be found in the LICENSE file. ============================================================================*/ // std includes #include // itk includes #include "itksys/SystemTools.hxx" // CTK includes #include "mitkCommandLineParser.h" // MITK includes #include #include #include #include #include std::string inFilename; std::string outFileName; mitk::Image::Pointer image; bool verbose(false); bool t1_absolute(false); bool t1_relative(false); bool t1_flash(false); bool t2(false); float k(1.0); float te(0); float rec_time(0); float relaxivity(0); float rel_time(0); void setupParser(mitkCommandLineParser& parser) { // set general information about your MiniApp parser.setCategory("Dynamic Data Analysis Tools"); parser.setTitle("MR Signal to Concentration Converter"); parser.setDescription("MiniApp that allows to convert a T1 or T2 signal image into a concentration image for perfusion analysis."); parser.setContributor("DKFZ MIC"); //! [create parser] //! [add arguments] // how should arguments be prefixed parser.setArgumentPrefix("--", "-"); // add each argument, unless specified otherwise each argument is optional // see mitkCommandLineParser::addArgument for more information parser.beginGroup("Required I/O parameters"); parser.addArgument( "input", "i", mitkCommandLineParser::File, "Input file", "input 3D+t image file", us::Any(), false, false, false, mitkCommandLineParser::Input); parser.addArgument("output", "o", mitkCommandLineParser::File, "Output file", "where to save the output concentration image.", us::Any(), false, false, false, mitkCommandLineParser::Output); parser.endGroup(); parser.beginGroup("Conversion parameters"); parser.addArgument( "t1-absolute", "", mitkCommandLineParser::Bool, "T1 absolute signal enhancement", "Activate conversion for T1 absolute signal enhancement."); parser.addArgument( "t1-relative", "", mitkCommandLineParser::Bool, "T1 relative signal enhancement", "Activate conversion for T1 relative signal enhancement."); parser.addArgument( "t1-flash", "", mitkCommandLineParser::Bool, "T1 turbo flash", "Activate specific conversion for T1 turbo flash sequences."); parser.addArgument( "t2", "", mitkCommandLineParser::Bool, "T2 signal conversion", "Activate conversion for T2 signal enhancement to concentration."); parser.addArgument( "k", "k", mitkCommandLineParser::Float, "Conversion factor k", "Needed for the following conversion modes: T1-absolute, T1-relative, T2. Default value is 1.", us::Any(1)); parser.addArgument( "recovery-time", "", mitkCommandLineParser::Float, "Recovery time", "Needed for the following conversion modes: T1-flash."); parser.addArgument( "relaxivity", "", mitkCommandLineParser::Float, "Relaxivity", "Needed for the following conversion modes: T1-flash."); parser.addArgument( "relaxation-time", "", mitkCommandLineParser::Float, "Relaxation time", "Needed for the following conversion modes: T1-flash."); parser.addArgument( "te", "", mitkCommandLineParser::Float, "Echo time TE", "Needed for the following conversion modes: T2.", us::Any(1)); parser.beginGroup("Optional parameters"); parser.addArgument( "verbose", "v", mitkCommandLineParser::Bool, "Verbose Output", "Whether to produce verbose output"); parser.addArgument("help", "h", mitkCommandLineParser::Bool, "Help:", "Show this help text"); parser.endGroup(); //! [add arguments] } bool configureApplicationSettings(std::map parsedArgs) { if (parsedArgs.size() == 0) return false; inFilename = us::any_cast(parsedArgs["input"]); outFileName = us::any_cast(parsedArgs["output"]); verbose = false; if (parsedArgs.count("verbose")) { verbose = us::any_cast(parsedArgs["verbose"]); } t1_absolute = false; if (parsedArgs.count("t1-absolute")) { t1_absolute = us::any_cast(parsedArgs["t1-absolute"]); } t1_relative = false; if (parsedArgs.count("t1-relative")) { t1_relative = us::any_cast(parsedArgs["t1-relative"]); } t1_flash = false; if (parsedArgs.count("t1-flash")) { t1_flash = us::any_cast(parsedArgs["t1-flash"]); } t2 = false; if (parsedArgs.count("t2")) { t2 = us::any_cast(parsedArgs["t2"]); } k = 0.0; if (parsedArgs.count("k")) { k = us::any_cast(parsedArgs["k"]); } relaxivity = 0.0; if (parsedArgs.count("relaxivity")) { relaxivity = us::any_cast(parsedArgs["relaxivity"]); } rec_time = 0.0; if (parsedArgs.count("recovery-time")) { rec_time = us::any_cast(parsedArgs["recovery-time"]); } rel_time = 0.0; if (parsedArgs.count("relaxation-time")) { rel_time = us::any_cast(parsedArgs["relaxation-time"]); } te = 0.0; if (parsedArgs.count("te")) { te = us::any_cast(parsedArgs["te"]); } //consistency checks int modeCount = 0; if (t1_absolute) ++modeCount; if (t1_flash) ++modeCount; if (t1_relative) ++modeCount; if (t2) ++modeCount; if (modeCount==0) { mitkThrow() << "Invalid program call. Please select the type of conversion."; } if (modeCount >1) { mitkThrow() << "Invalid program call. Please select only ONE type of conversion."; } if (!k && (t2 || t1_absolute || t1_relative)) { mitkThrow() << "Invalid program call. Please set 'k', if you use t1-absolute, t1-relative or t2."; } if (!te && t2) { mitkThrow() << "Invalid program call. Please set 'te', if you use t2 mode."; } if ((!rec_time||!rel_time||!relaxivity) && t1_flash) { mitkThrow() << "Invalid program call. Please set 'recovery-time', 'relaxation-time' and 'relaxivity', if you use t1-flash mode."; } return true; } void doConversion() { mitk::ConcentrationCurveGenerator::Pointer concentrationGen = mitk::ConcentrationCurveGenerator::New(); concentrationGen->SetDynamicImage(image); concentrationGen->SetisTurboFlashSequence(t1_flash); concentrationGen->SetAbsoluteSignalEnhancement(t1_absolute); concentrationGen->SetRelativeSignalEnhancement(t1_relative); concentrationGen->SetisT2weightedImage(t2); if (t1_flash) { concentrationGen->SetRecoveryTime(rec_time); concentrationGen->SetRelaxationTime(rel_time); concentrationGen->SetRelaxivity(relaxivity); } else if (t2) { concentrationGen->SetT2Factor(k); concentrationGen->SetT2EchoTime(te); } else { concentrationGen->SetFactor(k); } mitk::Image::Pointer concentrationImage = concentrationGen->GetConvertedImage(); mitk::IOUtil::Save(concentrationImage, outFileName); std::cout << "Store result: " << outFileName << std::endl; } int main(int argc, char* argv[]) { mitkCommandLineParser parser; setupParser(parser); const std::map& parsedArgs = parser.parseArguments(argc, argv); if (!configureApplicationSettings(parsedArgs)) { return EXIT_FAILURE; }; - mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (classic config)" }, { "MITK DICOM Reader" }); + mitk::PreferenceListReaderOptionsFunctor readerFilterFunctor = mitk::PreferenceListReaderOptionsFunctor({ "MITK DICOM Reader v2 (autoselect)" }, { "" }); // Show a help message if (parsedArgs.count("help") || parsedArgs.count("h")) { std::cout << parser.helpText(); return EXIT_SUCCESS; } //! [do processing] try { image = mitk::IOUtil::Load(inFilename, &readerFilterFunctor); std::cout << "Input: " << inFilename << std::endl; doConversion(); std::cout << "Processing finished." << std::endl; return EXIT_SUCCESS; } catch (const itk::ExceptionObject& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (const std::exception& e) { MITK_ERROR << e.what(); return EXIT_FAILURE; } catch (...) { MITK_ERROR << "Unexpected error encountered."; return EXIT_FAILURE; } }