diff --git a/Modules/DiffusionImaging/FiberTracking/cmdapps/TractographyEvaluation/AnchorBasedScoring.cpp b/Modules/DiffusionImaging/FiberTracking/cmdapps/TractographyEvaluation/AnchorBasedScoring.cpp
index 357c197a03..3eada727be 100755
--- a/Modules/DiffusionImaging/FiberTracking/cmdapps/TractographyEvaluation/AnchorBasedScoring.cpp
+++ b/Modules/DiffusionImaging/FiberTracking/cmdapps/TractographyEvaluation/AnchorBasedScoring.cpp
@@ -1,573 +1,575 @@
 /*===================================================================
 
 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 <mitkBaseData.h>
 #include <mitkImageCast.h>
 #include <mitkImageToItk.h>
 #include <metaCommand.h>
 #include <mitkCommandLineParser.h>
 #include <usAny.h>
 #include <mitkIOUtil.h>
 #include <itksys/SystemTools.hxx>
 #include <itkDirectory.h>
 #include <mitkFiberBundle.h>
 #include <mitkPreferenceListReaderOptionsFunctor.h>
 #include <itkImageFileWriter.h>
 #include <mitkPeakImage.h>
 #include <itkFitFibersToImageFilter.h>
 #include <boost/lexical_cast.hpp>
 #include <itkTractDensityImageFilter.h>
 
 typedef itksys::SystemTools ist;
 typedef itk::Point<float, 4> PointType4;
 typedef itk::Image< float, 4 >  PeakImgType;
 typedef itk::Image< unsigned char, 3 >  ItkUcharImageType;
 
 std::vector< mitk::FiberBundle::Pointer > CombineTractograms(std::vector< mitk::FiberBundle::Pointer > reference, std::vector< mitk::FiberBundle::Pointer > candidates, int skip=-1)
 {
   std::vector< mitk::FiberBundle::Pointer > fib;
   for (auto f : reference)
     fib.push_back(f);
 
   int c = 0;
   for (auto f : candidates)
   {
     if (c!=skip)
       fib.push_back(f);
     ++c;
   }
 
   return fib;
 }
 
 std::vector< std::string > get_file_list(const std::string& path, std::vector< std::string > extensions={".fib", ".trk"})
 {
   std::vector< std::string > file_list;
   itk::Directory::Pointer dir = itk::Directory::New();
 
   if (dir->Load(path.c_str()))
   {
     int n = dir->GetNumberOfFiles();
     for (int r = 0; r < n; r++)
     {
       const char *filename = dir->GetFile(r);
       std::string ext = ist::GetFilenameExtension(filename);
       for (auto e : extensions)
       {
         if (ext==e)
         {
           file_list.push_back(path + '/' + filename);
           break;
         }
       }
     }
   }
   return file_list;
 }
 
 /*!
 \brief Fits the tractogram to the input peak image by assigning a weight to each fiber (similar to https://doi.org/10.1016/j.neuroimage.2015.06.092).
 */
 int main(int argc, char* argv[])
 {
   mitkCommandLineParser parser;
 
   parser.setTitle("Anchor Based Scoring");
   parser.setCategory("Fiber Tracking Evaluation");
   parser.setDescription("");
   parser.setContributor("MIC");
 
   parser.setArgumentPrefix("--", "-");
   parser.addArgument("", "a", mitkCommandLineParser::InputFile, "Anchor tractogram:", "anchor tracts in one tractogram file", us::Any(), false);
   parser.addArgument("", "p", mitkCommandLineParser::InputFile, "Input peaks:", "input peak image", us::Any(), false);
   parser.addArgument("", "c", mitkCommandLineParser::InputDirectory, "Candidates folder:", "folder containing candidate tracts", us::Any(), false);
   parser.addArgument("", "o", mitkCommandLineParser::OutputDirectory, "Output folder:", "output folder", us::Any(), false);
 
   parser.addArgument("anchor_masks", "", mitkCommandLineParser::StringList, "Reference Masks:", "reference tract masks for accuracy evaluation");
   parser.addArgument("mask", "", mitkCommandLineParser::InputFile, "Mask image:", "scoring is only performed inside the mask image");
   parser.addArgument("greedy_add", "", mitkCommandLineParser::Bool, "Greedy:", "if enabled, the candidate tracts are not jointly fitted to the residual image but one after the other employing a greedy scheme", false);
   parser.addArgument("lambda", "", mitkCommandLineParser::Float, "Lambda:", "modifier for regularization", 0.1);
   parser.addArgument("filter_outliers", "", mitkCommandLineParser::Bool, "Filter outliers:", "perform second optimization run with an upper weight bound based on the first weight estimation (99% quantile)", false);
   parser.addArgument("regu", "", mitkCommandLineParser::String, "Regularization:", "MSM, Variance, VoxelVariance, Lasso, GroupLasso, GroupVariance, NONE (default)");
   parser.addArgument("use_num_streamlines", "", mitkCommandLineParser::Bool, "Use number of streamlines as score:", "Don't fit candidates, simply use number of streamlines per candidate as score", false);
   parser.addArgument("use_weights", "", mitkCommandLineParser::Bool, "Use input weights as score:", "Don't fit candidates, simply use first input streamline weight per candidate as score", false);
   parser.addArgument("filter_zero_weights", "", mitkCommandLineParser::Bool, "Filter zero-weights", "Remove streamlines with weight 0 from candidates", false);
 
   std::map<std::string, us::Any> parsedArgs = parser.parseArguments(argc, argv);
   if (parsedArgs.size()==0)
     return EXIT_FAILURE;
 
   std::string anchors_file = us::any_cast<std::string>(parsedArgs["a"]);
   std::string peak_file_name = us::any_cast<std::string>(parsedArgs["p"]);
   std::string candidate_tract_folder = us::any_cast<std::string>(parsedArgs["c"]);
   std::string out_folder = us::any_cast<std::string>(parsedArgs["o"]);
 
   bool greedy_add = false;
   if (parsedArgs.count("greedy_add"))
     greedy_add = us::any_cast<bool>(parsedArgs["greedy_add"]);
 
   float lambda = 0.1;
   if (parsedArgs.count("lambda"))
     lambda = us::any_cast<float>(parsedArgs["lambda"]);
 
   bool filter_outliers = false;
   if (parsedArgs.count("filter_outliers"))
     filter_outliers = us::any_cast<bool>(parsedArgs["filter_outliers"]);
 
   bool filter_zero_weights = false;
   if (parsedArgs.count("filter_zero_weights"))
     filter_zero_weights = us::any_cast<bool>(parsedArgs["filter_zero_weights"]);
 
   std::string mask_file = "";
   if (parsedArgs.count("mask"))
     mask_file = us::any_cast<std::string>(parsedArgs["mask"]);
 
   mitkCommandLineParser::StringContainerType anchor_mask_files_folders;
   if (parsedArgs.count("anchor_masks"))
     anchor_mask_files_folders = us::any_cast<mitkCommandLineParser::StringContainerType>(parsedArgs["anchor_masks"]);
 
   std::string regu = "NONE";
   if (parsedArgs.count("regu"))
     regu = us::any_cast<std::string>(parsedArgs["regu"]);
 
   bool use_weights = false;
   if (parsedArgs.count("use_weights"))
     use_weights = us::any_cast<bool>(parsedArgs["use_weights"]);
 
   bool use_num_streamlines = false;
   if (parsedArgs.count("use_num_streamlines"))
     use_num_streamlines = us::any_cast<bool>(parsedArgs["use_num_streamlines"]);
 
   try
   {
     itk::TimeProbe clock;
     clock.Start();
 
     if (!ist::PathExists(out_folder))
     {
       MITK_INFO << "Creating output directory";
       ist::MakeDirectory(out_folder);
     }
 
     MITK_INFO << "Loading data";
     std::streambuf *old = cout.rdbuf(); // <-- save
     std::stringstream ss;
     std::cout.rdbuf (ss.rdbuf());       // <-- redirect
 
     ofstream logfile;
     logfile.open (out_folder + "log.txt");
 
     itk::ImageFileWriter< PeakImgType >::Pointer peak_image_writer = itk::ImageFileWriter< PeakImgType >::New();
     mitk::PreferenceListReaderOptionsFunctor functor = mitk::PreferenceListReaderOptionsFunctor({"Peak Image", "Fiberbundles"}, {});
     mitk::Image::Pointer inputImage = dynamic_cast<mitk::PeakImage*>(mitk::IOUtil::Load(peak_file_name, &functor)[0].GetPointer());
 
     float minSpacing = 1;
     if(inputImage->GetGeometry()->GetSpacing()[0]<inputImage->GetGeometry()->GetSpacing()[1] && inputImage->GetGeometry()->GetSpacing()[0]<inputImage->GetGeometry()->GetSpacing()[2])
       minSpacing = inputImage->GetGeometry()->GetSpacing()[0];
     else if (inputImage->GetGeometry()->GetSpacing()[1] < inputImage->GetGeometry()->GetSpacing()[2])
       minSpacing = inputImage->GetGeometry()->GetSpacing()[1];
     else
       minSpacing = inputImage->GetGeometry()->GetSpacing()[2];
 
     // Load mask file. Fit is only performed inside the mask
     itk::FitFibersToImageFilter::UcharImgType::Pointer mask = nullptr;
     if (mask_file.compare("")!=0)
     {
       mitk::Image::Pointer mitk_mask = mitk::IOUtil::Load<mitk::Image>(mask_file);
       mitk::CastToItkImage(mitk_mask, mask);
     }
 
     // Load masks covering the true positives for evaluation purposes
     std::vector< itk::FitFibersToImageFilter::UcharImgType::Pointer > reference_masks;
     std::vector< std::string > anchor_mask_files;
     for (auto filename : anchor_mask_files_folders)
     {
       if (itksys::SystemTools::PathExists(filename))
       {
         auto list = get_file_list(filename, {".nrrd",".nii.gz",".nii"});
         for (auto f : list)
         {
+          MITK_INFO << f;
           itk::FitFibersToImageFilter::UcharImgType::Pointer ref_mask = nullptr;
           mitk::Image::Pointer ref_mitk_mask = mitk::IOUtil::Load<mitk::Image>(f);
           mitk::CastToItkImage(ref_mitk_mask, ref_mask);
           reference_masks.push_back(ref_mask);
           anchor_mask_files.push_back(f);
         }
       }
       else if (itksys::SystemTools::FileExists(filename))
       {
         anchor_mask_files.push_back(filename);
         itk::FitFibersToImageFilter::UcharImgType::Pointer ref_mask = nullptr;
         mitk::Image::Pointer ref_mitk_mask = mitk::IOUtil::Load<mitk::Image>(filename);
         mitk::CastToItkImage(ref_mitk_mask, ref_mask);
         reference_masks.push_back(ref_mask);
       }
     }
 
     // Load peak image
     typedef mitk::ImageToItk< PeakImgType > CasterType;
     CasterType::Pointer caster = CasterType::New();
     caster->SetInput(inputImage);
     caster->Update();
     PeakImgType::Pointer peak_image = caster->GetOutput();
 
     // Load all candidate tracts
     std::vector< std::string > candidate_tract_files = get_file_list(candidate_tract_folder);
     std::vector< mitk::FiberBundle::Pointer > input_candidates;
     for (std::string f : candidate_tract_files)
     {
       mitk::FiberBundle::Pointer fib = mitk::IOUtil::Load<mitk::FiberBundle>(f);
       if (fib.IsNull())
         continue;
       if (fib->GetNumFibers()<=0)
         continue;
       fib->ResampleLinear(minSpacing/10.0);
       input_candidates.push_back(fib);
     }
     std::cout.rdbuf (old);              // <-- restore
     MITK_INFO << "Loaded " << candidate_tract_files.size() << " candidate tracts.";
+    MITK_INFO << "Loaded " << reference_masks.size() << " reference masks.";
 
     double rmse = 0.0;
     int iteration = 0;
     std::string name = "NOANCHOR";
     // Load reference tractogram consisting of all known tracts
     std::vector< mitk::FiberBundle::Pointer > input_reference;
     mitk::FiberBundle::Pointer anchor_tractogram = mitk::IOUtil::Load<mitk::FiberBundle>(anchors_file);
     if ( !(anchor_tractogram.IsNull() || anchor_tractogram->GetNumFibers()==0) )
     {
       std::streambuf *old = cout.rdbuf(); // <-- save
       std::stringstream ss;
       std::cout.rdbuf (ss.rdbuf());       // <-- redirect
       anchor_tractogram->ResampleLinear(minSpacing/10.0);
       std::cout.rdbuf (old);              // <-- restore
       input_reference.push_back(anchor_tractogram);
 
       // Fit known tracts to peak image to obtain underexplained image
       MITK_INFO << "Fit anchor tracts";
       itk::FitFibersToImageFilter::Pointer fitter = itk::FitFibersToImageFilter::New();
       fitter->SetTractograms(input_reference);
       fitter->SetLambda(lambda);
       fitter->SetFilterOutliers(filter_outliers);
       fitter->SetPeakImage(peak_image);
       fitter->SetVerbose(true);
       fitter->SetResampleFibers(false);
       fitter->SetMaskImage(mask);
       fitter->SetRegularization(VnlCostFunction::REGU::NONE);
       fitter->Update();
       rmse = fitter->GetRMSE();
       vnl_vector<double> rms_diff = fitter->GetRmsDiffPerBundle();
       logfile << "RMS_DIFF: " << setprecision(5) << rms_diff[0] << " " << name << " RMSE: " << rmse << "\n";
 
       name = ist::GetFilenameWithoutExtension(anchors_file);
       mitk::FiberBundle::Pointer anchor_tracts = fitter->GetTractograms().at(0);
       anchor_tracts->SetFiberColors(255,255,255);
       mitk::IOUtil::Save(anchor_tracts, out_folder + boost::lexical_cast<std::string>((int)(100000*rms_diff[0])) + "_" + name + ".fib");
 
       peak_image = fitter->GetUnderexplainedImage();
       peak_image_writer->SetInput(peak_image);
       peak_image_writer->SetFileName(out_folder + "Residual_" + name + ".nii.gz");
       peak_image_writer->Update();
     }
 
     if (use_weights || use_num_streamlines)
     {
       MITK_INFO << "Using tract weights as scores";
       int c = 0;
       for (auto fib : input_candidates)
       {
         int mod = 1;
         double score = 0;
         if (use_weights)
         {
           score = fib->GetFiberWeight(0);
           mod = 100000;
         }
         else if (use_num_streamlines)
           score = fib->GetNumFibers();
         fib->ColorFibersByOrientation();
 
         std::string bundle_name = ist::GetFilenameWithoutExtension(candidate_tract_files.at(c));
 
         std::streambuf *old = cout.rdbuf(); // <-- save
         std::stringstream ss;
         std::cout.rdbuf (ss.rdbuf());       // <-- redirect
         mitk::IOUtil::Save(fib, out_folder + boost::lexical_cast<std::string>((int)(mod*score)) + "_" + bundle_name + ".fib");
 
         float best_overlap = 0;
         int best_overlap_index = -1;
         int m_idx = 0;
         for (auto ref_mask : reference_masks)
         {
           float overlap = fib->GetOverlap(ref_mask, false);
           if (overlap>best_overlap)
           {
             best_overlap = overlap;
             best_overlap_index = m_idx;
           }
           ++m_idx;
         }
 
         unsigned int num_voxels = 0;
         {
           itk::TractDensityImageFilter< ItkUcharImageType >::Pointer masks_filter = itk::TractDensityImageFilter< ItkUcharImageType >::New();
           masks_filter->SetInputImage(mask);
           masks_filter->SetBinaryOutput(true);
           masks_filter->SetFiberBundle(fib);
           masks_filter->SetUseImageGeometry(true);
           masks_filter->Update();
           num_voxels = masks_filter->GetNumCoveredVoxels();
         }
 
         double weight_sum = 0;
         for (int i=0; i<fib->GetNumFibers(); i++)
           weight_sum += fib->GetFiberWeight(i);
 
         std::cout.rdbuf (old);              // <-- restore
 
         logfile << "RMS_DIFF: " << setprecision(5) << score << " " << bundle_name << " " << num_voxels << " " << fib->GetNumFibers() << " " << weight_sum << "\n";
         if (best_overlap_index>=0)
           logfile << "Best_overlap: " << setprecision(5) << best_overlap << " " << ist::GetFilenameWithoutExtension(anchor_mask_files.at(best_overlap_index)) << "\n";
         else
           logfile << "No_overlap\n";
         ++c;
       }
 
     }
     else if (!greedy_add)
     {
       MITK_INFO << "Fit candidate tracts";
       itk::FitFibersToImageFilter::Pointer fitter = itk::FitFibersToImageFilter::New();
       fitter->SetLambda(lambda);
       fitter->SetFilterOutliers(filter_outliers);
       fitter->SetVerbose(true);
       fitter->SetPeakImage(peak_image);
       fitter->SetResampleFibers(false);
       fitter->SetMaskImage(mask);
       fitter->SetTractograms(input_candidates);
       fitter->SetFitIndividualFibers(true);
 
       if (regu=="MSM")
         fitter->SetRegularization(VnlCostFunction::REGU::MSM);
       else if (regu=="Variance")
         fitter->SetRegularization(VnlCostFunction::REGU::VARIANCE);
       else if (regu=="Lasso")
         fitter->SetRegularization(VnlCostFunction::REGU::LASSO);
       else if (regu=="VoxelVariance")
         fitter->SetRegularization(VnlCostFunction::REGU::VOXEL_VARIANCE);
       else if (regu=="GroupLasso")
         fitter->SetRegularization(VnlCostFunction::REGU::GROUP_LASSO);
       else if (regu=="GroupVariance")
         fitter->SetRegularization(VnlCostFunction::REGU::GROUP_VARIANCE);
       else if (regu=="NONE")
         fitter->SetRegularization(VnlCostFunction::REGU::NONE);
 
       fitter->Update();
       vnl_vector<double> rms_diff = fitter->GetRmsDiffPerBundle();
 
 //      vnl_vector<double> log_rms_diff = rms_diff-rms_diff.min_value() + 1;
 //      log_rms_diff = log_rms_diff.apply(std::log);
 //      log_rms_diff /= log_rms_diff.max_value();
       int c = 0;
       for (auto fib : input_candidates)
       {
 //        fib->SetFiberWeights( log_rms_diff[c] );
 //        fib->ColorFibersByOrientation();
 
         std::string bundle_name = ist::GetFilenameWithoutExtension(candidate_tract_files.at(c));
 
         std::streambuf *old = cout.rdbuf(); // <-- save
         std::stringstream ss;
         std::cout.rdbuf (ss.rdbuf());       // <-- redirect
         if (filter_zero_weights)
           fib = fib->FilterByWeights(0);
         mitk::IOUtil::Save(fib, out_folder + boost::lexical_cast<std::string>((int)(100000*rms_diff[c])) + "_" + bundle_name + ".fib");
 
         float best_overlap = 0;
         int best_overlap_index = -1;
         int m_idx = 0;
         for (auto ref_mask : reference_masks)
         {
           float overlap = fib->GetOverlap(ref_mask, false);
           if (overlap>best_overlap)
           {
             best_overlap = overlap;
             best_overlap_index = m_idx;
           }
           ++m_idx;
         }
 
         unsigned int num_voxels = 0;
         {
           itk::TractDensityImageFilter< ItkUcharImageType >::Pointer masks_filter = itk::TractDensityImageFilter< ItkUcharImageType >::New();
           masks_filter->SetInputImage(mask);
           masks_filter->SetBinaryOutput(true);
           masks_filter->SetFiberBundle(fib);
           masks_filter->SetUseImageGeometry(true);
           masks_filter->Update();
           num_voxels = masks_filter->GetNumCoveredVoxels();
         }
 
         double weight_sum = 0;
         for (int i=0; i<fib->GetNumFibers(); i++)
           weight_sum += fib->GetFiberWeight(i);
 
         std::cout.rdbuf (old);              // <-- restore
 
         logfile << "RMS_DIFF: " << setprecision(5) << rms_diff[c] << " " << bundle_name << " " << num_voxels << " " << fib->GetNumFibers() << " " << weight_sum << "\n";
         if (best_overlap_index>=0)
           logfile << "Best_overlap: " << setprecision(5) << best_overlap << " " << ist::GetFilenameWithoutExtension(anchor_mask_files.at(best_overlap_index)) << "\n";
         else
           logfile << "No_overlap\n";
 
         ++c;
       }
 
       mitk::FiberBundle::Pointer out_fib = mitk::FiberBundle::New();
       out_fib = out_fib->AddBundles(input_candidates);
       out_fib->ColorFibersByFiberWeights(false, true);
       mitk::IOUtil::Save(out_fib, out_folder + "AllCandidates.fib");
 
       peak_image = fitter->GetUnderexplainedImage();
       peak_image_writer->SetInput(peak_image);
       peak_image_writer->SetFileName(out_folder + "Residual_AllCandidates.nii.gz");
       peak_image_writer->Update();
     }
     else
     {
       MITK_INFO << "RMSE: " << setprecision(5) << rmse;
       //    fitter->SetPeakImage(peak_image);
 
       // Iteratively add candidate bundles in a greedy manner
       while (!input_candidates.empty())
       {
         double next_rmse = rmse;
         double num_peaks = 0;
         mitk::FiberBundle::Pointer best_candidate = nullptr;
         PeakImgType::Pointer best_candidate_peak_image = nullptr;
 
         for (int i=0; i<(int)input_candidates.size(); ++i)
         {
           // WHY NECESSARY AGAIN??
           itk::FitFibersToImageFilter::Pointer fitter = itk::FitFibersToImageFilter::New();
           fitter->SetLambda(lambda);
           fitter->SetFilterOutliers(filter_outliers);
           fitter->SetVerbose(false);
           fitter->SetPeakImage(peak_image);
           fitter->SetResampleFibers(false);
           fitter->SetMaskImage(mask);
           // ******************************
           fitter->SetTractograms({input_candidates.at(i)});
 
           std::streambuf *old = cout.rdbuf(); // <-- save
           std::stringstream ss;
           std::cout.rdbuf (ss.rdbuf());       // <-- redirect
           fitter->Update();
           std::cout.rdbuf (old);              // <-- restore
 
           double candidate_rmse = fitter->GetRMSE();
 
           if (candidate_rmse<next_rmse)
           {
             next_rmse = candidate_rmse;
             num_peaks = fitter->GetNumCoveredDirections();
             best_candidate = fitter->GetTractograms().at(0);
             best_candidate_peak_image = fitter->GetUnderexplainedImage();
           }
         }
 
         if (best_candidate.IsNull())
           break;
 
         //      fitter->SetPeakImage(peak_image);
         peak_image = best_candidate_peak_image;
 
         int i=0;
         std::vector< mitk::FiberBundle::Pointer > remaining_candidates;
         std::vector< std::string > remaining_candidate_files;
         for (auto fib : input_candidates)
         {
           if (fib!=best_candidate)
           {
             remaining_candidates.push_back(fib);
             remaining_candidate_files.push_back(candidate_tract_files.at(i));
           }
           else
             name = ist::GetFilenameWithoutExtension(candidate_tract_files.at(i));
           ++i;
         }
         input_candidates = remaining_candidates;
         candidate_tract_files = remaining_candidate_files;
 
         iteration++;
         std::streambuf *old = cout.rdbuf(); // <-- save
         std::stringstream ss;
         std::cout.rdbuf (ss.rdbuf());       // <-- redirect
         // Save winning candidate
         if (filter_zero_weights)
           best_candidate = best_candidate->FilterByWeights(0);
         mitk::IOUtil::Save(best_candidate, out_folder + boost::lexical_cast<std::string>(iteration) + "_" + name + ".fib");
         peak_image_writer->SetInput(peak_image);
         peak_image_writer->SetFileName(out_folder + boost::lexical_cast<std::string>(iteration) + "_" + name + ".nrrd");
         peak_image_writer->Update();
 
         // Calculate best overlap with reference masks for evaluation purposes
         float best_overlap = 0;
         int best_overlap_index = -1;
         i = 0;
         for (auto ref_mask : reference_masks)
         {
           float overlap = best_candidate->GetOverlap(ref_mask, false);
           if (overlap>best_overlap)
           {
             best_overlap = overlap;
             best_overlap_index = i;
           }
           ++i;
         }
         std::cout.rdbuf (old);              // <-- restore
 
         logfile << "RMSE: " << setprecision(5) << rmse << " " << name << " " << num_peaks << "\n";
         if (best_overlap_index>=0)
           logfile << "Best_overlap: " << setprecision(5) << best_overlap << " " << ist::GetFilenameWithoutExtension(anchor_mask_files.at(best_overlap_index)) << "\n";
         else
           logfile << "No_overlap\n";
       }
     }
 
     clock.Stop();
     int h = clock.GetTotal()/3600;
     int m = ((int)clock.GetTotal()%3600)/60;
     int s = (int)clock.GetTotal()%60;
     MITK_INFO << "Plausibility estimation took " << h << "h, " << m << "m and " << s << "s";
     logfile.close();
   }
   catch (itk::ExceptionObject e)
   {
     std::cout << e;
     return EXIT_FAILURE;
   }
   catch (std::exception e)
   {
     std::cout << e.what();
     return EXIT_FAILURE;
   }
   catch (...)
   {
     std::cout << "ERROR!?!";
     return EXIT_FAILURE;
   }
   return EXIT_SUCCESS;
 }