diff --git a/Modules/DiffusionImaging/DiffusionCmdApps/Tractography/RfTraining.cpp b/Modules/DiffusionImaging/DiffusionCmdApps/Tractography/RfTraining.cpp index eb145757f5..f7b942b649 100755 --- a/Modules/DiffusionImaging/DiffusionCmdApps/Tractography/RfTraining.cpp +++ b/Modules/DiffusionImaging/DiffusionCmdApps/Tractography/RfTraining.cpp @@ -1,238 +1,238 @@ /*=================================================================== 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 "mitkCommandLineParser.h" #include #include #include #include #include #include #include #include #include #include #define _USE_MATH_DEFINES #include /*! \brief Train random forest classifier for machine learning based streamline tractography */ int main(int argc, char* argv[]) { MITK_INFO << "RfTraining"; mitkCommandLineParser parser; parser.setTitle("Trains Random Forests for Machine Learning Based Tractography"); parser.setCategory("Fiber Tracking and Processing Methods"); parser.setDescription("Train random forest classifier for machine learning based streamline tractography"); parser.setContributor("MIC"); parser.setArgumentPrefix("--", "-"); parser.beginGroup("1. Mandatory arguments:"); parser.addArgument("", "i", mitkCommandLineParser::StringList, "DWIs:", "input diffusion-weighted images", us::Any(), false); parser.addArgument("", "t", mitkCommandLineParser::StringList, "Tractograms:", "input training tractograms", us::Any(), false); parser.addArgument("", "o", mitkCommandLineParser::OutputFile, "Forest:", "output random forest (HDF5)", us::Any(), false); parser.endGroup(); parser.beginGroup("2. Additional input images:"); parser.addArgument("masks", "", mitkCommandLineParser::StringList, "Masks:", "restrict training using a binary mask image", us::Any()); parser.addArgument("wm_masks", "", mitkCommandLineParser::StringList, "WM-Masks:", "if no binary white matter mask is specified, the envelope of the input tractogram is used", us::Any()); parser.addArgument("volume_modification_images", "", mitkCommandLineParser::StringList, "Volume modification images:", "specify a list of float images that modify the fiber density", us::Any()); parser.addArgument("additional_feature_images", "", mitkCommandLineParser::StringList, "Additional feature images:", "specify a list of float images that hold additional features (float)", us::Any()); parser.endGroup(); parser.beginGroup("3. Forest parameters:"); parser.addArgument("num_trees", "", mitkCommandLineParser::Int, "Number of trees:", "number of trees", 30); parser.addArgument("max_tree_depth", "", mitkCommandLineParser::Int, "Max. tree depth:", "maximum tree depth", 25); parser.addArgument("sample_fraction", "", mitkCommandLineParser::Float, "Sample fraction:", "fraction of samples used per tree", 0.7); parser.endGroup(); parser.beginGroup("4. Feature parameters:"); parser.addArgument("use_sh_features", "", mitkCommandLineParser::Bool, "Use SH features:", "use SH features", false); parser.addArgument("sampling_distance", "", mitkCommandLineParser::Float, "Sampling distance:", "resampling parameter for the input tractogram in mm (determines number of white-matter samples)", us::Any()); parser.addArgument("max_wm_samples", "", mitkCommandLineParser::Int, "Max. num. WM samples:", "upper limit for the number of WM samples"); parser.addArgument("num_gm_samples", "", mitkCommandLineParser::Int, "Number of gray matter samples per voxel:", "Number of gray matter samples per voxel", us::Any()); parser.endGroup(); std::map parsedArgs = parser.parseArguments(argc, argv); if (parsedArgs.size()==0) return EXIT_FAILURE; bool shfeatures = false; if (parsedArgs.count("use_sh_features")) shfeatures = us::any_cast(parsedArgs["use_sh_features"]); mitkCommandLineParser::StringContainerType imageFiles = us::any_cast(parsedArgs["i"]); mitkCommandLineParser::StringContainerType wmMaskFiles; if (parsedArgs.count("wm_masks")) wmMaskFiles = us::any_cast(parsedArgs["wm_masks"]); mitkCommandLineParser::StringContainerType volModFiles; if (parsedArgs.count("volume_modification_images")) volModFiles = us::any_cast(parsedArgs["volume_modification_images"]); mitkCommandLineParser::StringContainerType addFeatFiles; if (parsedArgs.count("additional_feature_images")) addFeatFiles = us::any_cast(parsedArgs["additional_feature_images"]); mitkCommandLineParser::StringContainerType maskFiles; if (parsedArgs.count("masks")) maskFiles = us::any_cast(parsedArgs["masks"]); std::string forestFile = us::any_cast(parsedArgs["o"]); mitkCommandLineParser::StringContainerType tractogramFiles; - if (parsedArgs.count("tractograms")) + if (parsedArgs.count("t")) tractogramFiles = us::any_cast(parsedArgs["t"]); int num_trees = 30; if (parsedArgs.count("num_trees")) num_trees = us::any_cast(parsedArgs["num_trees"]); int gm_samples = -1; if (parsedArgs.count("num_gm_samples")) gm_samples = us::any_cast(parsedArgs["num_gm_samples"]); float sampling_distance = -1; if (parsedArgs.count("sampling_distance")) sampling_distance = us::any_cast(parsedArgs["sampling_distance"]); int max_tree_depth = 25; if (parsedArgs.count("max_tree_depth")) max_tree_depth = us::any_cast(parsedArgs["max_tree_depth"]); double sample_fraction = 0.7; if (parsedArgs.count("sample_fraction")) sample_fraction = us::any_cast(parsedArgs["sample_fraction"]); int maxWmSamples = -1; if (parsedArgs.count("max_wm_samples")) maxWmSamples = us::any_cast(parsedArgs["max_wm_samples"]); MITK_INFO << "loading diffusion-weighted images"; std::vector< mitk::Image::Pointer > rawData; mitk::PreferenceListReaderOptionsFunctor functor = mitk::PreferenceListReaderOptionsFunctor({"Diffusion Weighted Images"}, {}); for (auto imgFile : imageFiles) { auto dwi = mitk::IOUtil::Load(imgFile, &functor); rawData.push_back(dwi); } typedef itk::Image ItkFloatImgType; typedef itk::Image ItkUcharImgType; MITK_INFO << "loading mask images"; std::vector< ItkUcharImgType::Pointer > maskImageVector; for (auto maskFile : maskFiles) { mitk::Image::Pointer img = mitk::IOUtil::Load(maskFile); ItkUcharImgType::Pointer mask = ItkUcharImgType::New(); mitk::CastToItkImage(img, mask); maskImageVector.push_back(mask); } MITK_INFO << "loading white matter mask images"; std::vector< ItkUcharImgType::Pointer > wmMaskImageVector; for (auto wmFile : wmMaskFiles) { mitk::Image::Pointer img = mitk::IOUtil::Load(wmFile); ItkUcharImgType::Pointer wmmask = ItkUcharImgType::New(); mitk::CastToItkImage(img, wmmask); wmMaskImageVector.push_back(wmmask); } MITK_INFO << "loading tractograms"; std::vector< mitk::FiberBundle::Pointer > tractograms; for (auto tractFile : tractogramFiles) { mitk::FiberBundle::Pointer fib = mitk::IOUtil::Load(tractFile); tractograms.push_back(fib); } MITK_INFO << "loading white volume modification images"; std::vector< ItkFloatImgType::Pointer > volumeModImages; for (auto file : volModFiles) { mitk::Image::Pointer img = mitk::IOUtil::Load(file); ItkFloatImgType::Pointer itkimg = ItkFloatImgType::New(); mitk::CastToItkImage(img, itkimg); volumeModImages.push_back(itkimg); } MITK_INFO << "loading additional feature images"; std::vector< std::vector< ItkFloatImgType::Pointer > > addFeatImages; for (std::size_t i=0; i()); int c = 0; for (auto file : addFeatFiles) { mitk::Image::Pointer img = mitk::IOUtil::Load(file); ItkFloatImgType::Pointer itkimg = ItkFloatImgType::New(); mitk::CastToItkImage(img, itkimg); addFeatImages.at(c%addFeatImages.size()).push_back(itkimg); c++; } mitk::TractographyForest::Pointer forest = nullptr; if (shfeatures) { mitk::TrackingHandlerRandomForest<6,28> forestHandler; forestHandler.SetDwis(rawData); forestHandler.SetMaskImages(maskImageVector); forestHandler.SetWhiteMatterImages(wmMaskImageVector); forestHandler.SetFiberVolumeModImages(volumeModImages); forestHandler.SetAdditionalFeatureImages(addFeatImages); forestHandler.SetTractograms(tractograms); forestHandler.SetNumTrees(num_trees); forestHandler.SetMaxTreeDepth(max_tree_depth); forestHandler.SetGrayMatterSamplesPerVoxel(gm_samples); forestHandler.SetSampleFraction(sample_fraction); forestHandler.SetFiberSamplingStep(sampling_distance); forestHandler.SetMaxNumWmSamples(maxWmSamples); forestHandler.StartTraining(); forest = forestHandler.GetForest(); } else { mitk::TrackingHandlerRandomForest<6,100> forestHandler; forestHandler.SetDwis(rawData); forestHandler.SetMaskImages(maskImageVector); forestHandler.SetWhiteMatterImages(wmMaskImageVector); forestHandler.SetFiberVolumeModImages(volumeModImages); forestHandler.SetAdditionalFeatureImages(addFeatImages); forestHandler.SetTractograms(tractograms); forestHandler.SetNumTrees(num_trees); forestHandler.SetMaxTreeDepth(max_tree_depth); forestHandler.SetGrayMatterSamplesPerVoxel(gm_samples); forestHandler.SetSampleFraction(sample_fraction); forestHandler.SetFiberSamplingStep(sampling_distance); forestHandler.SetMaxNumWmSamples(maxWmSamples); forestHandler.StartTraining(); forest = forestHandler.GetForest(); } mitk::IOUtil::Save(forest, forestFile); return EXIT_SUCCESS; } diff --git a/Modules/DiffusionImaging/DiffusionCmdApps/Tractography/StreamlineTractography.cpp b/Modules/DiffusionImaging/DiffusionCmdApps/Tractography/StreamlineTractography.cpp index 567b57d90c..bfd69f92c4 100755 --- a/Modules/DiffusionImaging/DiffusionCmdApps/Tractography/StreamlineTractography.cpp +++ b/Modules/DiffusionImaging/DiffusionCmdApps/Tractography/StreamlineTractography.cpp @@ -1,562 +1,562 @@ /*=================================================================== 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 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #define _USE_MATH_DEFINES #include const int numOdfSamples = 200; typedef itk::Image< itk::Vector< float, numOdfSamples > , 3 > SampledShImageType; /*! \brief */ int main(int argc, char* argv[]) { mitkCommandLineParser parser; parser.setTitle("Streamline Tractography"); parser.setCategory("Fiber Tracking and Processing Methods"); parser.setDescription("Perform streamline tractography"); parser.setContributor("MIC"); // parameters fo all methods parser.setArgumentPrefix("--", "-"); parser.beginGroup("1. Mandatory arguments:"); parser.addArgument("", "i", mitkCommandLineParser::StringList, "Input:", "input image (multiple possible for 'DetTensor' algorithm)", us::Any(), false); parser.addArgument("", "o", mitkCommandLineParser::OutputDirectory, "Output:", "output fiberbundle/probability map", us::Any(), false); parser.addArgument("algorithm", "", mitkCommandLineParser::String, "Algorithm:", "which algorithm to use (Peaks, DetTensor, ProbTensor, DetODF, ProbODF, DetRF, ProbRF)", us::Any(), false); parser.endGroup(); parser.beginGroup("2. Seeding:"); parser.addArgument("seeds", "", mitkCommandLineParser::Int, "Seeds per voxel:", "number of seed points per voxel", 1); parser.addArgument("seed_image", "", mitkCommandLineParser::String, "Seed image:", "mask image defining seed voxels", us::Any()); parser.addArgument("trials_per_seed", "", mitkCommandLineParser::Int, "Max. trials per seed:", "try each seed N times until a valid streamline is obtained (only for probabilistic tractography)", 10); parser.addArgument("max_tracts", "", mitkCommandLineParser::Int, "Max. number of tracts:", "tractography is stopped if the reconstructed number of tracts is exceeded", -1); parser.endGroup(); parser.beginGroup("3. Tractography constraints:"); parser.addArgument("tracking_mask", "", mitkCommandLineParser::String, "Mask image:", "streamlines leaving the mask will stop immediately", us::Any()); parser.addArgument("stop_image", "", mitkCommandLineParser::String, "Stop ROI image:", "streamlines entering the mask will stop immediately", us::Any()); parser.addArgument("exclusion_image", "", mitkCommandLineParser::String, "Exclusion ROI image:", "streamlines entering the mask will be discarded", us::Any()); parser.addArgument("ep_constraint", "", mitkCommandLineParser::String, "Endpoint constraint:", "determines which fibers are accepted based on their endpoint location - options are NONE, EPS_IN_TARGET, EPS_IN_TARGET_LABELDIFF, EPS_IN_SEED_AND_TARGET, MIN_ONE_EP_IN_TARGET, ONE_EP_IN_TARGET and NO_EP_IN_TARGET", us::Any()); parser.addArgument("target_image", "", mitkCommandLineParser::String, "Target ROI image:", "effact depends on the chosen endpoint constraint (option ep_constraint)", us::Any()); parser.endGroup(); parser.beginGroup("4. Streamline integration parameters:"); parser.addArgument("sharpen_odfs", "", mitkCommandLineParser::Bool, "SHarpen ODFs:", "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 narurally much sharper."); parser.addArgument("cutoff", "", mitkCommandLineParser::Float, "Cutoff:", "set the FA, GFA or Peak amplitude cutoff for terminating tracks", 0.1); parser.addArgument("odf_cutoff", "", mitkCommandLineParser::Float, "ODF Cutoff:", "threshold on the ODF magnitude. this is useful in case of CSD fODF tractography.", 0.0); parser.addArgument("step_size", "", mitkCommandLineParser::Float, "Step size:", "step size (in voxels)", 0.5); parser.addArgument("min_tract_length", "", mitkCommandLineParser::Float, "Min. tract length:", "minimum fiber length (in mm)", 20); parser.addArgument("angular_threshold", "", mitkCommandLineParser::Float, "Angular threshold:", "angular threshold between two successive steps, (default: 90° * step_size, minimum 15°)"); parser.addArgument("loop_check", "", mitkCommandLineParser::Float, "Check for loops:", "threshold on angular stdev over the last 4 voxel lengths"); parser.endGroup(); parser.beginGroup("5. Tractography prior:"); parser.addArgument("prior_image", "", mitkCommandLineParser::String, "Peak prior:", "tractography prior in thr for of a peak image", us::Any()); parser.addArgument("prior_weight", "", mitkCommandLineParser::Float, "Prior weight", "weighting factor between prior and data.", 0.5); parser.addArgument("restrict_to_prior", "", mitkCommandLineParser::Bool, "Restrict to prior:", "restrict tractography to regions where the prior is valid."); parser.addArgument("new_directions_from_prior", "", mitkCommandLineParser::Bool, "New directios from prior:", "the prior can create directions where there are none in the data."); parser.endGroup(); parser.beginGroup("6. Neighborhood sampling:"); parser.addArgument("num_samples", "", mitkCommandLineParser::Int, "Num. neighborhood samples:", "number of neighborhood samples that are use to determine the next progression direction", 0); parser.addArgument("sampling_distance", "", mitkCommandLineParser::Float, "Sampling distance:", "distance of neighborhood sampling points (in voxels)", 0.25); parser.addArgument("use_stop_votes", "", mitkCommandLineParser::Bool, "Use stop votes:", "use stop votes"); parser.addArgument("use_only_forward_samples", "", mitkCommandLineParser::Bool, "Use only forward samples:", "use only forward samples"); parser.endGroup(); parser.beginGroup("7. Tensor tractography specific:"); parser.addArgument("tend_f", "", mitkCommandLineParser::Float, "Weight f", "weighting factor between first eigenvector (f=1 equals FACT tracking) and input vector dependent direction (f=0).", 1.0); parser.addArgument("tend_g", "", mitkCommandLineParser::Float, "Weight g", "weighting factor between input vector (g=0) and tensor deflection (g=1 equals TEND tracking)", 0.0); parser.endGroup(); parser.beginGroup("8. Random forest tractography specific:"); parser.addArgument("forest", "", mitkCommandLineParser::String, "Forest:", "input random forest (HDF5 file)", us::Any()); parser.addArgument("use_sh_features", "", mitkCommandLineParser::Bool, "Use SH features:", "use SH features"); parser.endGroup(); parser.beginGroup("9. Additional input:"); parser.addArgument("additional_images", "", mitkCommandLineParser::StringList, "Additional images:", "specify a list of float images that hold additional information (FA, GFA, additional features for RF tractography)", us::Any()); parser.endGroup(); parser.beginGroup("10. Misc:"); parser.addArgument("flip_x", "", mitkCommandLineParser::Bool, "Flip X:", "multiply x-coordinate of direction proposal by -1"); parser.addArgument("flip_y", "", mitkCommandLineParser::Bool, "Flip Y:", "multiply y-coordinate of direction proposal by -1"); parser.addArgument("flip_z", "", mitkCommandLineParser::Bool, "Flip Z:", "multiply z-coordinate of direction proposal by -1"); parser.addArgument("no_data_interpolation", "", mitkCommandLineParser::Bool, "Don't interpolate input data:", "don't interpolate input image values"); parser.addArgument("no_mask_interpolation", "", mitkCommandLineParser::Bool, "Don't interpolate masks:", "don't interpolate mask image values"); parser.addArgument("compress", "", mitkCommandLineParser::Float, "Compress:", "compress output fibers using the given error threshold (in mm)"); parser.endGroup(); std::map parsedArgs = parser.parseArguments(argc, argv); if (parsedArgs.size()==0) return EXIT_FAILURE; mitkCommandLineParser::StringContainerType input_files = us::any_cast(parsedArgs["i"]); std::string outFile = us::any_cast(parsedArgs["o"]); std::string algorithm = us::any_cast(parsedArgs["algorithm"]); std::string prior_image = ""; if (parsedArgs.count("prior_image")) prior_image = us::any_cast(parsedArgs["prior_image"]); float prior_weight = 0.5; if (parsedArgs.count("prior_weight")) prior_weight = us::any_cast(parsedArgs["prior_weight"]); bool restrict_to_prior = false; if (parsedArgs.count("restrict_to_prior")) restrict_to_prior = us::any_cast(parsedArgs["restrict_to_prior"]); bool new_directions_from_prior = false; if (parsedArgs.count("new_directions_from_prior")) new_directions_from_prior = us::any_cast(parsedArgs["new_directions_from_prior"]); bool sharpen_odfs = false; if (parsedArgs.count("sharpen_odfs")) sharpen_odfs = us::any_cast(parsedArgs["sharpen_odfs"]); bool interpolate = true; if (parsedArgs.count("no_data_interpolation")) interpolate = !us::any_cast(parsedArgs["no_data_interpolation"]); bool mask_interpolation = true; if (parsedArgs.count("no_mask_interpolation")) interpolate = !us::any_cast(parsedArgs["no_mask_interpolation"]); bool use_sh_features = false; if (parsedArgs.count("use_sh_features")) use_sh_features = us::any_cast(parsedArgs["use_sh_features"]); bool use_stop_votes = false; if (parsedArgs.count("use_stop_votes")) use_stop_votes = us::any_cast(parsedArgs["use_stop_votes"]); bool use_only_forward_samples = false; if (parsedArgs.count("use_only_forward_samples")) use_only_forward_samples = us::any_cast(parsedArgs["use_only_forward_samples"]); bool flip_x = false; if (parsedArgs.count("flip_x")) flip_x = us::any_cast(parsedArgs["flip_x"]); bool flip_y = false; if (parsedArgs.count("flip_y")) flip_y = us::any_cast(parsedArgs["flip_y"]); bool flip_z = false; if (parsedArgs.count("flip_z")) flip_z = us::any_cast(parsedArgs["flip_z"]); bool apply_image_rotation = false; if (parsedArgs.count("apply_image_rotation")) apply_image_rotation = us::any_cast(parsedArgs["apply_image_rotation"]); float compress = -1; if (parsedArgs.count("compress")) compress = us::any_cast(parsedArgs["compress"]); float min_tract_length = 20; if (parsedArgs.count("min_tract_length")) min_tract_length = us::any_cast(parsedArgs["min_tract_length"]); float loop_check = -1; if (parsedArgs.count("loop_check")) loop_check = us::any_cast(parsedArgs["loop_check"]); std::string forestFile; if (parsedArgs.count("forest")) forestFile = us::any_cast(parsedArgs["forest"]); std::string maskFile = ""; if (parsedArgs.count("tracking_mask")) maskFile = us::any_cast(parsedArgs["tracking_mask"]); std::string seedFile = ""; if (parsedArgs.count("seed_image")) seedFile = us::any_cast(parsedArgs["seed_image"]); std::string targetFile = ""; if (parsedArgs.count("target_image")) targetFile = us::any_cast(parsedArgs["target_image"]); std::string exclusionFile = ""; if (parsedArgs.count("exclusion_image")) exclusionFile = us::any_cast(parsedArgs["exclusion_image"]); std::string stopFile = ""; if (parsedArgs.count("stop_image")) stopFile = us::any_cast(parsedArgs["stop_image"]); std::string ep_constraint = "NONE"; if (parsedArgs.count("ep_constraint")) ep_constraint = us::any_cast(parsedArgs["ep_constraint"]); float cutoff = 0.1f; if (parsedArgs.count("cutoff")) cutoff = us::any_cast(parsedArgs["cutoff"]); float odf_cutoff = 0.0; if (parsedArgs.count("odf_cutoff")) odf_cutoff = us::any_cast(parsedArgs["odf_cutoff"]); float stepsize = -1; if (parsedArgs.count("step_size")) stepsize = us::any_cast(parsedArgs["step_size"]); float sampling_distance = -1; if (parsedArgs.count("sampling_distance")) sampling_distance = us::any_cast(parsedArgs["sampling_distance"]); unsigned int num_samples = 0; if (parsedArgs.count("num_samples")) - num_samples = us::any_cast(parsedArgs["num_samples"]); + num_samples = static_cast(us::any_cast(parsedArgs["num_samples"])); int num_seeds = 1; if (parsedArgs.count("seeds")) num_seeds = us::any_cast(parsedArgs["seeds"]); unsigned int trials_per_seed = 10; if (parsedArgs.count("trials_per_seed")) - trials_per_seed = us::any_cast(parsedArgs["trials_per_seed"]); + trials_per_seed = static_cast(us::any_cast(parsedArgs["trials_per_seed"])); float tend_f = 1; if (parsedArgs.count("tend_f")) tend_f = us::any_cast(parsedArgs["tend_f"]); float tend_g = 0; if (parsedArgs.count("tend_g")) tend_g = us::any_cast(parsedArgs["tend_g"]); float angular_threshold = -1; if (parsedArgs.count("angular_threshold")) angular_threshold = us::any_cast(parsedArgs["angular_threshold"]); int max_tracts = -1; if (parsedArgs.count("max_tracts")) max_tracts = us::any_cast(parsedArgs["max_tracts"]); std::string ext = itksys::SystemTools::GetFilenameExtension(outFile); if (ext != ".fib" && ext != ".trk") { MITK_INFO << "Output file format not supported. Use one of .fib, .trk, .nii, .nii.gz, .nrrd"; return EXIT_FAILURE; } // LOAD DATASETS mitkCommandLineParser::StringContainerType addFiles; if (parsedArgs.count("additional_images")) addFiles = us::any_cast(parsedArgs["additional_images"]); typedef itk::Image ItkFloatImgType; ItkFloatImgType::Pointer mask = nullptr; if (!maskFile.empty()) { MITK_INFO << "loading mask image"; mitk::Image::Pointer img = mitk::IOUtil::Load(maskFile); mask = ItkFloatImgType::New(); mitk::CastToItkImage(img, mask); } ItkFloatImgType::Pointer seed = nullptr; if (!seedFile.empty()) { MITK_INFO << "loading seed ROI image"; mitk::Image::Pointer img = mitk::IOUtil::Load(seedFile); seed = ItkFloatImgType::New(); mitk::CastToItkImage(img, seed); } ItkFloatImgType::Pointer stop = nullptr; if (!stopFile.empty()) { MITK_INFO << "loading stop ROI image"; mitk::Image::Pointer img = mitk::IOUtil::Load(stopFile); stop = ItkFloatImgType::New(); mitk::CastToItkImage(img, stop); } ItkFloatImgType::Pointer target = nullptr; if (!targetFile.empty()) { MITK_INFO << "loading target ROI image"; mitk::Image::Pointer img = mitk::IOUtil::Load(targetFile); target = ItkFloatImgType::New(); mitk::CastToItkImage(img, target); } ItkFloatImgType::Pointer exclusion = nullptr; if (!exclusionFile.empty()) { MITK_INFO << "loading exclusion ROI image"; mitk::Image::Pointer img = mitk::IOUtil::Load(exclusionFile); exclusion = ItkFloatImgType::New(); mitk::CastToItkImage(img, exclusion); } MITK_INFO << "loading additional images"; std::vector< std::vector< ItkFloatImgType::Pointer > > addImages; addImages.push_back(std::vector< ItkFloatImgType::Pointer >()); for (auto file : addFiles) { mitk::Image::Pointer img = mitk::IOUtil::Load(file); ItkFloatImgType::Pointer itkimg = ItkFloatImgType::New(); mitk::CastToItkImage(img, itkimg); addImages.at(0).push_back(itkimg); } // ////////////////////////////////////////////////////////////////// // omp_set_num_threads(1); typedef itk::StreamlineTrackingFilter TrackerType; TrackerType::Pointer tracker = TrackerType::New(); if (!prior_image.empty()) { mitk::PreferenceListReaderOptionsFunctor functor = mitk::PreferenceListReaderOptionsFunctor({"Peak Image"}, {}); mitk::PeakImage::Pointer priorImage = mitk::IOUtil::Load(prior_image, &functor); if (priorImage.IsNull()) { MITK_INFO << "Only peak images are supported as prior at the moment!"; return EXIT_FAILURE; } mitk::TrackingDataHandler* priorhandler = new mitk::TrackingHandlerPeaks(); typedef mitk::ImageToItk< mitk::TrackingHandlerPeaks::PeakImgType > CasterType; CasterType::Pointer caster = CasterType::New(); caster->SetInput(priorImage); caster->Update(); mitk::TrackingHandlerPeaks::PeakImgType::Pointer itkImg = caster->GetOutput(); dynamic_cast(priorhandler)->SetPeakImage(itkImg); dynamic_cast(priorhandler)->SetPeakThreshold(0.0); dynamic_cast(priorhandler)->SetInterpolate(interpolate); dynamic_cast(priorhandler)->SetMode(mitk::TrackingDataHandler::MODE::DETERMINISTIC); tracker->SetTrackingPriorHandler(priorhandler); tracker->SetTrackingPriorWeight(prior_weight); tracker->SetTrackingPriorAsMask(restrict_to_prior); tracker->SetIntroduceDirectionsFromPrior(new_directions_from_prior); } mitk::TrackingDataHandler* handler; if (algorithm == "DetRF" || algorithm == "ProbRF") { mitk::TractographyForest::Pointer forest = mitk::IOUtil::Load(forestFile); if (forest.IsNull()) mitkThrow() << "Forest file " << forestFile << " could not be read."; mitk::PreferenceListReaderOptionsFunctor functor = mitk::PreferenceListReaderOptionsFunctor({"Diffusion Weighted Images"}, {}); auto input = mitk::IOUtil::Load(input_files.at(0), &functor); if (use_sh_features) { handler = new mitk::TrackingHandlerRandomForest<6,28>(); dynamic_cast*>(handler)->SetForest(forest); dynamic_cast*>(handler)->AddDwi(input); dynamic_cast*>(handler)->SetAdditionalFeatureImages(addImages); } else { handler = new mitk::TrackingHandlerRandomForest<6,100>(); dynamic_cast*>(handler)->SetForest(forest); dynamic_cast*>(handler)->AddDwi(input); dynamic_cast*>(handler)->SetAdditionalFeatureImages(addImages); } if (algorithm == "ProbRF") handler->SetMode(mitk::TrackingDataHandler::MODE::PROBABILISTIC); } else if (algorithm == "Peaks") { handler = new mitk::TrackingHandlerPeaks(); MITK_INFO << "loading input peak image"; mitk::Image::Pointer mitkImage = mitk::IOUtil::Load(input_files.at(0)); mitk::TrackingHandlerPeaks::PeakImgType::Pointer itkImg = mitk::convert::GetItkPeakFromPeakImage(mitkImage); dynamic_cast(handler)->SetPeakImage(itkImg); dynamic_cast(handler)->SetApplyDirectionMatrix(apply_image_rotation); dynamic_cast(handler)->SetPeakThreshold(cutoff); } else if (algorithm == "DetTensor") { handler = new mitk::TrackingHandlerTensor(); MITK_INFO << "loading input tensor images"; std::vector< mitk::Image::Pointer > input_images; for (unsigned int i=0; i(input_files.at(i)); mitk::TensorImage::ItkTensorImageType::Pointer itkImg = mitk::convert::GetItkTensorFromTensorImage(mitkImage); dynamic_cast(handler)->AddTensorImage(itkImg.GetPointer()); } dynamic_cast(handler)->SetFaThreshold(cutoff); dynamic_cast(handler)->SetF(tend_f); dynamic_cast(handler)->SetG(tend_g); if (addImages.at(0).size()>0) dynamic_cast(handler)->SetFaImage(addImages.at(0).at(0)); } else if (algorithm == "DetODF" || algorithm == "ProbODF" || algorithm == "ProbTensor") { handler = new mitk::TrackingHandlerOdf(); mitk::OdfImage::ItkOdfImageType::Pointer itkImg = nullptr; if (algorithm == "ProbTensor") { MITK_INFO << "Converting Tensor to ODF image"; auto input = mitk::IOUtil::Load(input_files.at(0)); itkImg = mitk::convert::GetItkOdfFromTensorImage(input); sharpen_odfs = true; odf_cutoff = 0; dynamic_cast(handler)->SetIsOdfFromTensor(true); } else { mitk::PreferenceListReaderOptionsFunctor functor = mitk::PreferenceListReaderOptionsFunctor({"SH Image", "ODF Image"}, {}); auto input = mitk::IOUtil::Load(input_files.at(0), &functor)[0]; if (dynamic_cast(input.GetPointer())) { MITK_INFO << "Converting SH to ODF image"; mitk::Image::Pointer mitkImg = dynamic_cast(input.GetPointer()); itkImg = mitk::convert::GetItkOdfFromShImage(mitkImg); } else if (dynamic_cast(input.GetPointer())) { mitk::Image::Pointer mitkImg = dynamic_cast(input.GetPointer()); itkImg = mitk::convert::GetItkOdfFromOdfImage(mitkImg); } else mitkThrow() << ""; } dynamic_cast(handler)->SetOdfImage(itkImg); dynamic_cast(handler)->SetGfaThreshold(cutoff); dynamic_cast(handler)->SetOdfThreshold(odf_cutoff); dynamic_cast(handler)->SetSharpenOdfs(sharpen_odfs); if (algorithm == "ProbODF" || algorithm == "ProbTensor") dynamic_cast(handler)->SetMode(mitk::TrackingHandlerOdf::MODE::PROBABILISTIC); if (addImages.at(0).size()>0) dynamic_cast(handler)->SetGfaImage(addImages.at(0).at(0)); } else { MITK_INFO << "Unknown tractography algorithm (" + algorithm+"). Known types are Peaks, DetTensor, ProbTensor, DetODF, ProbODF, DetRF, ProbRF."; return EXIT_FAILURE; } handler->SetInterpolate(interpolate); handler->SetFlipX(flip_x); handler->SetFlipY(flip_y); handler->SetFlipZ(flip_z); if (ep_constraint=="NONE") tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::NONE); else if (ep_constraint=="EPS_IN_TARGET") tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::EPS_IN_TARGET); else if (ep_constraint=="EPS_IN_TARGET_LABELDIFF") tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::EPS_IN_TARGET_LABELDIFF); else if (ep_constraint=="EPS_IN_SEED_AND_TARGET") tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::EPS_IN_SEED_AND_TARGET); else if (ep_constraint=="MIN_ONE_EP_IN_TARGET") tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::MIN_ONE_EP_IN_TARGET); else if (ep_constraint=="ONE_EP_IN_TARGET") tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::ONE_EP_IN_TARGET); else if (ep_constraint=="NO_EP_IN_TARGET") tracker->SetEndpointConstraint(itk::StreamlineTrackingFilter::EndpointConstraints::NO_EP_IN_TARGET); MITK_INFO << "Tractography algorithm: " << algorithm; tracker->SetInterpolateMasks(mask_interpolation); tracker->SetNumberOfSamples(num_samples); tracker->SetAngularThreshold(angular_threshold); tracker->SetMaskImage(mask); tracker->SetSeedImage(seed); tracker->SetStoppingRegions(stop); tracker->SetTargetRegions(target); tracker->SetExclusionRegions(exclusion); tracker->SetSeedsPerVoxel(num_seeds); tracker->SetStepSize(stepsize); tracker->SetSamplingDistance(sampling_distance); tracker->SetUseStopVotes(use_stop_votes); tracker->SetOnlyForwardSamples(use_only_forward_samples); tracker->SetLoopCheck(loop_check); tracker->SetMaxNumTracts(max_tracts); tracker->SetTrialsPerSeed(trials_per_seed); tracker->SetTrackingHandler(handler); if (ext != ".fib" && ext != ".trk") tracker->SetUseOutputProbabilityMap(true); tracker->SetMinTractLength(min_tract_length); tracker->Update(); if (ext == ".fib" || ext == ".trk") { vtkSmartPointer< vtkPolyData > poly = tracker->GetFiberPolyData(); mitk::FiberBundle::Pointer outFib = mitk::FiberBundle::New(poly); if (compress > 0) outFib->Compress(compress); mitk::IOUtil::Save(outFib, outFile); } else { TrackerType::ItkDoubleImgType::Pointer outImg = tracker->GetOutputProbabilityMap(); mitk::Image::Pointer img = mitk::Image::New(); img->InitializeByItk(outImg.GetPointer()); img->SetVolume(outImg->GetBufferPointer()); if (ext != ".nii" && ext != ".nii.gz" && ext != ".nrrd") outFile += ".nii.gz"; mitk::IOUtil::Save(img, outFile); } delete handler; return EXIT_SUCCESS; }