diff --git a/Modules/DiffusionCmdApps/FiberProcessing/TractometryComparison.cpp b/Modules/DiffusionCmdApps/FiberProcessing/TractometryComparison.cpp
index 8b980a8..8a42e74 100644
--- a/Modules/DiffusionCmdApps/FiberProcessing/TractometryComparison.cpp
+++ b/Modules/DiffusionCmdApps/FiberProcessing/TractometryComparison.cpp
@@ -1,133 +1,137 @@
 /*===================================================================
 
 The Medical Imaging Interaction Toolkit (MITK)
 
 Copyright (c) German Cancer Research Center.
 
 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 <mitkIOUtil.h>
 #include <metaCommand.h>
 #include "mitkDiffusionCommandLineParser.h"
 #include <usAny.h>
 #include <mitkIOUtil.h>
 #include <mitkLexicalCast.h>
 #include <mitkCoreObjectFactory.h>
 #include <mitkPlanarFigure.h>
 #include <mitkPlanarFigureComposite.h>
 #include <mitkFiberBundle.h>
 #include <mitkDiffusionDataIOHelper.h>
 #include <mitkTractometry.h>
 #include <itksys/SystemTools.hxx>
 #include <itkTractParcellationFilter.h>
 
 #define _USE_MATH_DEFINES
 #include <math.h>
 
 /*!
 \brief Join multiple tractograms
 */
 int main(int argc, char* argv[])
 {
   mitkDiffusionCommandLineParser parser;
 
   parser.setTitle("Fiber Statistics");
   parser.setCategory("Fiber Tracking and Processing Methods");
   parser.setContributor("MIC");
   parser.setDescription("Output statistics about fiber lengths, weights, etc. to a file.");
 
   parser.setArgumentPrefix("--", "-");
   parser.addArgument("tracts", "", mitkDiffusionCommandLineParser::StringList, "Input tracts:", "input tracts", us::Any(), false);
   parser.addArgument("images", "", mitkDiffusionCommandLineParser::StringList, "Input images:", "input images", us::Any(), false);
   parser.addArgument("out_file", "", mitkDiffusionCommandLineParser::String, "Output File:", "output file", us::Any(), false);
+  parser.addArgument("num_parcels", "", mitkDiffusionCommandLineParser::Int, "Number of parcels:", "", 15);
 
   std::map<std::string, us::Any> parsedArgs = parser.parseArguments(argc, argv);
   if (parsedArgs.size()==0)
     return EXIT_FAILURE;
 
   mitkDiffusionCommandLineParser::StringContainerType inFibs = us::any_cast<mitkDiffusionCommandLineParser::StringContainerType>(parsedArgs["tracts"]);
   mitkDiffusionCommandLineParser::StringContainerType inImages = us::any_cast<mitkDiffusionCommandLineParser::StringContainerType>(parsedArgs["images"]);
   std::string outfile = us::any_cast<std::string>(parsedArgs["out_file"]);
-  int num_parcels = 20;
+
+  int num_parcels = 15;
+  if (parsedArgs.count("num_parcels"))
+    num_parcels = us::any_cast<int>(parsedArgs["num_parcels"]);
 
   try
   {
 
     std::vector< std::string > fib_names, img_names;
     auto input_tracts = mitk::DiffusionDataIOHelper::load_fibs(inFibs, &fib_names);
     auto input_images = mitk::DiffusionDataIOHelper::load_itk_images<itk::Image<float, 3>>(inImages, &img_names);
 
     bool add_header = !itksys::SystemTools::FileExists(outfile, true);
 
 
     std::ofstream statistics_file;
     statistics_file.open (outfile, std::ios_base::app);
     if (add_header)
       statistics_file << "method;tract_file;image_file;parcel;value" << std::endl;
 
     auto ref = input_tracts.at(0)->GetDeepCopy();
     for (unsigned int i=0; i<inFibs.size(); ++i)
     {
       auto fib = input_tracts.at(i);
       fib->ResampleSpline(1.0);
 
       {
         auto output = mitk::Tractometry::StaticResamplingTractometry(input_images.at(i), fib->GetDeepCopy(), num_parcels, ref);
         for (unsigned int r=0; r<output.rows(); ++r)
           for (unsigned int c=0; c<output.cols(); ++c)
             statistics_file << "StaticResamplingTractometry;" << fib_names.at(i) << ";" << img_names.at(i) << ";" << boost::lexical_cast<std::string>(r) << ";" << boost::lexical_cast<std::string>(output.get(r,c)) << std::endl;
       }
 
       {
         auto output = mitk::Tractometry::NearestCentroidPointTractometry(input_images.at(i), fib->GetDeepCopy(), num_parcels, 1, 99, ref);
         for (unsigned int r=0; r<output.size(); ++r)
           for (unsigned int c=0; c<output.at(r).size(); ++c)
             statistics_file << "NearestCentroidPointTractometry;" << fib_names.at(i) << ";" << img_names.at(i) << ";" << boost::lexical_cast<std::string>(r) << ";" << boost::lexical_cast<std::string>(output.at(r).get(c)) << std::endl;
       }
       {
         itk::TractParcellationFilter< itk::Image<unsigned char, 3>, itk::Image<float, 3> >::Pointer parcellator = itk::TractParcellationFilter< itk::Image<unsigned char, 3>, itk::Image<float, 3> >::New();
         parcellator->SetInputImage(input_images.at(i));
         parcellator->SetNumParcels(num_parcels);
         parcellator->SetInputTract(fib->GetDeepCopy());
         parcellator->SetReferenceTract(ref);
         parcellator->Update();
         itk::Image<unsigned char, 3>::Pointer out_image_pp = parcellator->GetOutput(1);
 
         itk::ImageRegionConstIterator< itk::Image<float, 3> > it(input_images.at(i), input_images.at(i)->GetLargestPossibleRegion());
         itk::ImageRegionConstIterator< itk::Image<unsigned char, 3> > it2(out_image_pp, out_image_pp->GetLargestPossibleRegion());
         while (!it.IsAtEnd()) {
           if (it2.Get()>0)
             statistics_file << "TractParcellationFilter;" << fib_names.at(i) << ";" << img_names.at(i) << ";" << boost::lexical_cast<std::string>(it2.Get()-1) << ";" << boost::lexical_cast<std::string>(it.Get()) << std::endl;
           ++it;
           ++it2;
         }
       }
     }
 
     statistics_file.close();
   }
   catch (const itk::ExceptionObject& e)
   {
     std::cout << e.what();
     return EXIT_FAILURE;
   }
   catch (std::exception& e)
   {
     std::cout << e.what();
     return EXIT_FAILURE;
   }
   catch (...)
   {
     std::cout << "ERROR!?!";
     return EXIT_FAILURE;
   }
   return EXIT_SUCCESS;
 }