diff --git a/CMakeExternals/MITKData.cmake b/CMakeExternals/MITKData.cmake
index 5158c2452d..eaacdac1da 100644
--- a/CMakeExternals/MITKData.cmake
+++ b/CMakeExternals/MITKData.cmake
@@ -1,35 +1,35 @@
 #-----------------------------------------------------------------------------
 # MITK Data
 #-----------------------------------------------------------------------------
 
 # Sanity checks
 if(DEFINED MITK_DATA_DIR AND NOT EXISTS ${MITK_DATA_DIR})
   message(FATAL_ERROR "MITK_DATA_DIR variable is defined but corresponds to non-existing directory")
 endif()
 
 set(proj MITK-Data)
 set(proj_DEPENDENCIES)
 set(MITK-Data_DEPENDS ${proj})
 
 if(BUILD_TESTING)
-  set(revision_tag 5f90eb5e)
+  set(revision_tag 248b7888)
 #                  ^^^^^^^^  these are just to check correct length of hash part
 
   ExternalProject_Add(${proj}
     URL ${MITK_THIRDPARTY_DOWNLOAD_PREFIX_URL}/MITK-Data_${revision_tag}.tar.gz
     UPDATE_COMMAND ""
     CONFIGURE_COMMAND ""
     BUILD_COMMAND ""
     INSTALL_COMMAND ""
     DEPENDS ${proj_DEPENDENCIES}
   )
 
   set(MITK_DATA_DIR ${ep_source_dir}/${proj})
 
 else()
 
   mitkMacroEmptyExternalProject(${proj} "${proj_DEPENDENCIES}")
 
 endif(BUILD_TESTING)
 
 
diff --git a/Modules/DiffusionImaging/FiberTracking/Algorithms/itkStreamlineTrackingFilter.cpp b/Modules/DiffusionImaging/FiberTracking/Algorithms/itkStreamlineTrackingFilter.cpp
index 4a19131757..fcc0f997e6 100644
--- a/Modules/DiffusionImaging/FiberTracking/Algorithms/itkStreamlineTrackingFilter.cpp
+++ b/Modules/DiffusionImaging/FiberTracking/Algorithms/itkStreamlineTrackingFilter.cpp
@@ -1,883 +1,883 @@
 /*===================================================================
 
 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.
 
 ===================================================================*/
 
 #ifndef __itkStreamlineTrackingFilter_txx
 #define __itkStreamlineTrackingFilter_txx
 
 #include <time.h>
 #include <stdio.h>
 #include <stdlib.h>
 
 #include "itkStreamlineTrackingFilter.h"
 #include <itkImageRegionConstIterator.h>
 #include <itkImageRegionConstIteratorWithIndex.h>
 #include <itkImageRegionIterator.h>
 
 #define _USE_MATH_DEFINES
 #include <math.h>
 
 namespace itk {
 
 //#define QBALL_RECON_PI       M_PI
 
 template< class TTensorPixelType, class TPDPixelType>
 StreamlineTrackingFilter< TTensorPixelType,
 TPDPixelType>
 ::StreamlineTrackingFilter():
     m_FaThreshold(0.2),
     m_StepSize(1),
     m_MaxLength(10000),
     m_SeedsPerVoxel(1),
     m_F(1.0),
     m_G(0.0),
     m_Interpolate(true),
     m_MinTractLength(0.0),
     m_ResampleFibers(false)
 {
     // At least 1 inputs is necessary for a vector image.
     // For images added one at a time we need at least six
     this->SetNumberOfRequiredInputs( 1 );
     this->SetNumberOfIndexedInputs(3);
 }
 
 template< class TTensorPixelType,
           class TPDPixelType>
 double StreamlineTrackingFilter< TTensorPixelType,
 TPDPixelType>
 ::RoundToNearest(double num) {
     return (num > 0.0) ? floor(num + 0.5) : ceil(num - 0.5);
 }
 
 template< class TTensorPixelType,
           class TPDPixelType>
 void StreamlineTrackingFilter< TTensorPixelType,
 TPDPixelType>
 ::BeforeThreadedGenerateData()
 {
     m_FiberPolyData = FiberPolyDataType::New();
     m_Points = vtkPoints::New();
     m_Cells = vtkCellArray::New();
 
     InputImageType* inputImage = static_cast< InputImageType * >( this->ProcessObject::GetInput(0) );
     m_ImageSize.resize(3);
     m_ImageSize[0] = inputImage->GetLargestPossibleRegion().GetSize()[0];
     m_ImageSize[1] = inputImage->GetLargestPossibleRegion().GetSize()[1];
     m_ImageSize[2] = inputImage->GetLargestPossibleRegion().GetSize()[2];
 
     if (m_ImageSize[0]<3 || m_ImageSize[1]<3 || m_ImageSize[2]<3)
         m_Interpolate = false;
 
     m_ImageSpacing.resize(3);
     m_ImageSpacing[0] = inputImage->GetSpacing()[0];
     m_ImageSpacing[1] = inputImage->GetSpacing()[1];
     m_ImageSpacing[2] = inputImage->GetSpacing()[2];
 
     float minSpacing;
     if(m_ImageSpacing[0]<m_ImageSpacing[1] && m_ImageSpacing[0]<m_ImageSpacing[2])
         minSpacing = m_ImageSpacing[0];
     else if (m_ImageSpacing[1] < m_ImageSpacing[2])
         minSpacing = m_ImageSpacing[1];
     else
         minSpacing = m_ImageSpacing[2];
     if (m_StepSize<0.1*minSpacing)
         m_StepSize = 0.1*minSpacing;
 
     if (m_ResampleFibers)
         m_PointPistance = 0.5*minSpacing;
 
     m_PolyDataContainer = itk::VectorContainer< int, FiberPolyDataType >::New();
     for (unsigned int i=0; i<this->GetNumberOfThreads(); i++)
     {
         FiberPolyDataType poly = FiberPolyDataType::New();
         m_PolyDataContainer->InsertElement(i, poly);
     }
 
     if (m_SeedImage.IsNull())
     {
         // initialize mask image
         m_SeedImage = ItkUcharImgType::New();
         m_SeedImage->SetSpacing( inputImage->GetSpacing() );
         m_SeedImage->SetOrigin( inputImage->GetOrigin() );
         m_SeedImage->SetDirection( inputImage->GetDirection() );
         m_SeedImage->SetRegions( inputImage->GetLargestPossibleRegion() );
         m_SeedImage->Allocate();
         m_SeedImage->FillBuffer(1);
     }
 
     if (m_MaskImage.IsNull())
     {
         // initialize mask image
         m_MaskImage = ItkUcharImgType::New();
         m_MaskImage->SetSpacing( inputImage->GetSpacing() );
         m_MaskImage->SetOrigin( inputImage->GetOrigin() );
         m_MaskImage->SetDirection( inputImage->GetDirection() );
         m_MaskImage->SetRegions( inputImage->GetLargestPossibleRegion() );
         m_MaskImage->Allocate();
         m_MaskImage->FillBuffer(1);
     }
 
     bool useUserFaImage = true;
     if (m_FaImage.IsNull())
     {
         m_FaImage = ItkFloatImgType::New();
         m_FaImage->SetSpacing( inputImage->GetSpacing() );
         m_FaImage->SetOrigin( inputImage->GetOrigin() );
         m_FaImage->SetDirection( inputImage->GetDirection() );
         m_FaImage->SetRegions( inputImage->GetLargestPossibleRegion() );
         m_FaImage->Allocate();
         m_FaImage->FillBuffer(0.0);
         useUserFaImage = false;
     }
 
     m_NumberOfInputs = 0;
     for (unsigned int i=0; i<this->GetNumberOfIndexedInputs(); i++)
     {
         if (this->ProcessObject::GetInput(i)==NULL)
             break;
 
         ItkPDImgType::Pointer pdImage = ItkPDImgType::New();
         pdImage->SetSpacing( inputImage->GetSpacing() );
         pdImage->SetOrigin( inputImage->GetOrigin() );
         pdImage->SetDirection( inputImage->GetDirection() );
         pdImage->SetRegions( inputImage->GetLargestPossibleRegion() );
         pdImage->Allocate();
         m_PdImage.push_back(pdImage);
 
         ItkFloatImgType::Pointer emaxImage = ItkFloatImgType::New();
         emaxImage->SetSpacing( inputImage->GetSpacing() );
         emaxImage->SetOrigin( inputImage->GetOrigin() );
         emaxImage->SetDirection( inputImage->GetDirection() );
         emaxImage->SetRegions( inputImage->GetLargestPossibleRegion() );
         emaxImage->Allocate();
         emaxImage->FillBuffer(1.0);
         m_EmaxImage.push_back(emaxImage);
 
         typename InputImageType::Pointer inputImage = static_cast< InputImageType * >( this->ProcessObject::GetInput(i) );
         m_InputImage.push_back(inputImage);
 
         m_NumberOfInputs++;
     }
     MITK_INFO << "Processing " << m_NumberOfInputs << " tensor files";
 
     typedef itk::DiffusionTensor3D<TTensorPixelType>    TensorType;
     typename TensorType::EigenValuesArrayType eigenvalues;
     typename TensorType::EigenVectorsMatrixType eigenvectors;
 
 
     for (int x=0; x<m_ImageSize[0]; x++)
         for (int y=0; y<m_ImageSize[1]; y++)
             for (int z=0; z<m_ImageSize[2]; z++)
             {
                 typename InputImageType::IndexType index;
                 index[0] = x; index[1] = y; index[2] = z;
                 for (int i=0; i<m_NumberOfInputs; i++)
                 {
                     typename InputImageType::PixelType tensor = m_InputImage.at(i)->GetPixel(index);
                     vnl_vector_fixed<double,3> dir;
                     tensor.ComputeEigenAnalysis(eigenvalues, eigenvectors);
                     dir[0] = eigenvectors(2, 0);
                     dir[1] = eigenvectors(2, 1);
                     dir[2] = eigenvectors(2, 2);
                     dir.normalize();
                     m_PdImage.at(i)->SetPixel(index, dir);
                     if (!useUserFaImage)
                         m_FaImage->SetPixel(index, m_FaImage->GetPixel(index)+tensor.GetFractionalAnisotropy());
                     m_EmaxImage.at(i)->SetPixel(index, 2/eigenvalues[2]);
                 }
                 if (!useUserFaImage)
                     m_FaImage->SetPixel(index, m_FaImage->GetPixel(index)/m_NumberOfInputs);
             }
 
     if (m_Interpolate)
         std::cout << "StreamlineTrackingFilter: using trilinear interpolation" << std::endl;
     else
     {
         if (m_MinCurvatureRadius<0.0)
             m_MinCurvatureRadius = 0.1*minSpacing;
 
         std::cout << "StreamlineTrackingFilter: using nearest neighbor interpolation" << std::endl;
     }
 
     if (m_MinCurvatureRadius<0.0)
         m_MinCurvatureRadius = 0.5*minSpacing;
 
     std::cout << "StreamlineTrackingFilter: Min. curvature radius: " << m_MinCurvatureRadius << std::endl;
     std::cout << "StreamlineTrackingFilter: FA threshold: " << m_FaThreshold << std::endl;
     std::cout << "StreamlineTrackingFilter: stepsize: " << m_StepSize << " mm" << std::endl;
     std::cout << "StreamlineTrackingFilter: f: " << m_F << std::endl;
     std::cout << "StreamlineTrackingFilter: g: " << m_G << std::endl;
-    std::cout << "StreamlineTrackingFilter: starting streamline tracking" << std::endl;
+    std::cout << "StreamlineTrackingFilter: starting streamline tracking using " << this->GetNumberOfThreads() << " threads." << std::endl;
 }
 
 template< class TTensorPixelType, class TPDPixelType>
 void StreamlineTrackingFilter< TTensorPixelType, TPDPixelType>
 ::CalculateNewPosition(itk::ContinuousIndex<double, 3>& pos, vnl_vector_fixed<double,3>& dir, typename InputImageType::IndexType& index)
 {
     vnl_matrix_fixed< double, 3, 3 > rot = m_InputImage.at(0)->GetDirection().GetTranspose();
     dir = rot*dir;
     if (true)
     {
         dir *= m_StepSize;
         pos[0] += dir[0]/m_ImageSpacing[0];
         pos[1] += dir[1]/m_ImageSpacing[1];
         pos[2] += dir[2]/m_ImageSpacing[2];
         index[0] = RoundToNearest(pos[0]);
         index[1] = RoundToNearest(pos[1]);
         index[2] = RoundToNearest(pos[2]);
     }
     else
     {
         dir[0] /= m_ImageSpacing[0];
         dir[1] /= m_ImageSpacing[1];
         dir[2] /= m_ImageSpacing[2];
 
         int smallest = 0;
         float x = 100000;
         if (dir[0]>0)
         {
             if (fabs(fabs(RoundToNearest(pos[0])-pos[0])-0.5)>mitk::eps)
                 x = fabs(pos[0]-RoundToNearest(pos[0])-0.5)/dir[0];
             else
                 x = fabs(pos[0]-std::ceil(pos[0])-0.5)/dir[0];
         }
         else if (dir[0]<0)
         {
             if (fabs(fabs(RoundToNearest(pos[0])-pos[0])-0.5)>mitk::eps)
                 x = -fabs(pos[0]-RoundToNearest(pos[0])+0.5)/dir[0];
             else
                 x = -fabs(pos[0]-std::floor(pos[0])+0.5)/dir[0];
         }
         float s = x;
 
         float y = 100000;
         if (dir[1]>0)
         {
             if (fabs(fabs(RoundToNearest(pos[1])-pos[1])-0.5)>mitk::eps)
                 y = fabs(pos[1]-RoundToNearest(pos[1])-0.5)/dir[1];
             else
                 y = fabs(pos[1]-std::ceil(pos[1])-0.5)/dir[1];
         }
         else if (dir[1]<0)
         {
             if (fabs(fabs(RoundToNearest(pos[1])-pos[1])-0.5)>mitk::eps)
                 y = -fabs(pos[1]-RoundToNearest(pos[1])+0.5)/dir[1];
             else
                 y = -fabs(pos[1]-std::floor(pos[1])+0.5)/dir[1];
         }
         if (s>y)
         {
             s=y;
             smallest = 1;
         }
 
         float z = 100000;
         if (dir[2]>0)
         {
             if (fabs(fabs(RoundToNearest(pos[2])-pos[2])-0.5)>mitk::eps)
                 z = fabs(pos[2]-RoundToNearest(pos[2])-0.5)/dir[2];
             else
                 z = fabs(pos[2]-std::ceil(pos[2])-0.5)/dir[2];
         }
         else if (dir[2]<0)
         {
             if (fabs(fabs(RoundToNearest(pos[2])-pos[2])-0.5)>mitk::eps)
                 z = -fabs(pos[2]-RoundToNearest(pos[2])+0.5)/dir[2];
             else
                 z = -fabs(pos[2]-std::floor(pos[2])+0.5)/dir[2];
         }
         if (s>z)
         {
             s=z;
             smallest = 2;
         }
 
         //        MITK_INFO << "---------------------------------------------";
         //        MITK_INFO << "s: " << s;
         //        MITK_INFO << "dir: " << dir;
         //        MITK_INFO << "old: " << pos[0] << ", " << pos[1] << ", " << pos[2];
 
         pos[0] += dir[0]*s;
         pos[1] += dir[1]*s;
         pos[2] += dir[2]*s;
 
         switch (smallest)
         {
         case 0:
             if (dir[0]<0)
                 index[0] = std::floor(pos[0]);
             else
                 index[0] = std::ceil(pos[0]);
             index[1] = RoundToNearest(pos[1]);
             index[2] = RoundToNearest(pos[2]);
             break;
 
         case 1:
             if (dir[1]<0)
                 index[1] = std::floor(pos[1]);
             else
                 index[1] = std::ceil(pos[1]);
             index[0] = RoundToNearest(pos[0]);
             index[2] = RoundToNearest(pos[2]);
             break;
 
         case 2:
             if (dir[2]<0)
                 index[2] = std::floor(pos[2]);
             else
                 index[2] = std::ceil(pos[2]);
             index[1] = RoundToNearest(pos[1]);
             index[0] = RoundToNearest(pos[0]);
         }
 
         //        float x = 100000;
         //        if (dir[0]>0)
         //            x = fabs(pos[0]-RoundToNearest(pos[0])-0.5)/dir[0];
         //        else if (dir[0]<0)
         //            x = -fabs(pos[0]-RoundToNearest(pos[0])+0.5)/dir[0];
         //        float s = x;
 
         //        float y = 100000;
         //        if (dir[1]>0)
         //            y = fabs(pos[1]-RoundToNearest(pos[1])-0.5)/dir[1];
         //        else if (dir[1]<0)
         //            y = -fabs(pos[1]-RoundToNearest(pos[1])+0.5)/dir[1];
         //        if (s>y)
         //            s=y;
 
         //        float z = 100000;
         //        if (dir[2]>0)
         //            z = fabs(pos[2]-RoundToNearest(pos[2])-0.5)/dir[2];
         //        else if (dir[2]<0)
         //            z = -fabs(pos[2]-RoundToNearest(pos[2])+0.5)/dir[2];
 
         //        if (s>z)
         //            s=z;
         //        s *= 1.001;
 
         //        pos[0] += dir[0]*s;
         //        pos[1] += dir[1]*s;
         //        pos[2] += dir[2]*s;
 
         //        index[0] = RoundToNearest(pos[0]);
         //        index[1] = RoundToNearest(pos[1]);
         //        index[2] = RoundToNearest(pos[2]);
 
         //        MITK_INFO << "new: " << pos[0] << ", " << pos[1] << ", " << pos[2];
     }
 }
 
 template< class TTensorPixelType, class TPDPixelType>
 bool StreamlineTrackingFilter< TTensorPixelType, TPDPixelType>
 ::IsValidPosition(itk::ContinuousIndex<double, 3>& pos, typename InputImageType::IndexType &index, vnl_vector_fixed< float, 8 >& interpWeights, int imageIdx)
 {
     if (!m_InputImage.at(imageIdx)->GetLargestPossibleRegion().IsInside(index) || m_MaskImage->GetPixel(index)==0)
         return false;
 
     if (m_Interpolate)
     {
         float frac_x = pos[0] - index[0];
         float frac_y = pos[1] - index[1];
         float frac_z = pos[2] - index[2];
 
         if (frac_x<0)
         {
             index[0] -= 1;
             frac_x += 1;
         }
         if (frac_y<0)
         {
             index[1] -= 1;
             frac_y += 1;
         }
         if (frac_z<0)
         {
             index[2] -= 1;
             frac_z += 1;
         }
 
         frac_x = 1-frac_x;
         frac_y = 1-frac_y;
         frac_z = 1-frac_z;
 
         // int coordinates inside image?
         if (index[0] < 0 || index[0] >= m_ImageSize[0]-1)
             return false;
         if (index[1] < 0 || index[1] >= m_ImageSize[1]-1)
             return false;
         if (index[2] < 0 || index[2] >= m_ImageSize[2]-1)
             return false;
 
         interpWeights[0] = (  frac_x)*(  frac_y)*(  frac_z);
         interpWeights[1] = (1-frac_x)*(  frac_y)*(  frac_z);
         interpWeights[2] = (  frac_x)*(1-frac_y)*(  frac_z);
         interpWeights[3] = (  frac_x)*(  frac_y)*(1-frac_z);
         interpWeights[4] = (1-frac_x)*(1-frac_y)*(  frac_z);
         interpWeights[5] = (  frac_x)*(1-frac_y)*(1-frac_z);
         interpWeights[6] = (1-frac_x)*(  frac_y)*(1-frac_z);
         interpWeights[7] = (1-frac_x)*(1-frac_y)*(1-frac_z);
 
         typename InputImageType::IndexType tmpIdx;
         float FA = m_FaImage->GetPixel(index) * interpWeights[0];
         tmpIdx = index; tmpIdx[0]++;
         FA +=  m_FaImage->GetPixel(tmpIdx) * interpWeights[1];
         tmpIdx = index; tmpIdx[1]++;
         FA +=  m_FaImage->GetPixel(tmpIdx) * interpWeights[2];
         tmpIdx = index; tmpIdx[2]++;
         FA +=  m_FaImage->GetPixel(tmpIdx) * interpWeights[3];
         tmpIdx = index; tmpIdx[0]++; tmpIdx[1]++;
         FA +=  m_FaImage->GetPixel(tmpIdx) * interpWeights[4];
         tmpIdx = index; tmpIdx[1]++; tmpIdx[2]++;
         FA +=  m_FaImage->GetPixel(tmpIdx) * interpWeights[5];
         tmpIdx = index; tmpIdx[2]++; tmpIdx[0]++;
         FA +=  m_FaImage->GetPixel(tmpIdx) * interpWeights[6];
         tmpIdx = index; tmpIdx[0]++; tmpIdx[1]++; tmpIdx[2]++;
         FA +=  m_FaImage->GetPixel(tmpIdx) * interpWeights[7];
 
         if (FA<m_FaThreshold)
             return false;
     }
     else if (m_FaImage->GetPixel(index)<m_FaThreshold)
         return false;
 
     return true;
 }
 
 template< class TTensorPixelType, class TPDPixelType>
 float StreamlineTrackingFilter< TTensorPixelType, TPDPixelType>
 ::FollowStreamline(itk::ContinuousIndex<double, 3> pos, int dirSign, vtkPoints* points, std::vector< vtkIdType >& ids, int imageIdx)
 {
     float tractLength = 0;
     typedef itk::DiffusionTensor3D<TTensorPixelType>    TensorType;
     typename TensorType::EigenValuesArrayType eigenvalues;
     typename TensorType::EigenVectorsMatrixType eigenvectors;
     vnl_vector_fixed< float, 8 > interpWeights;
 
     typename InputImageType::IndexType index, indexOld;
     indexOld[0] = -1; indexOld[1] = -1; indexOld[2] = -1;
     itk::Point<double> worldPos;
     float distance = 0;
     float distanceInVoxel = 0;
 
     // starting index and direction
     index[0] = RoundToNearest(pos[0]);
     index[1] = RoundToNearest(pos[1]);
     index[2] = RoundToNearest(pos[2]);
 
     vnl_vector_fixed<double,3> dir = m_PdImage.at(imageIdx)->GetPixel(index);
     dir *= dirSign;                     // reverse direction
     vnl_vector_fixed<double,3> dirOld = dir;
     if (dir.magnitude()<mitk::eps)
         return tractLength;
 
     for (int step=0; step< m_MaxLength/2; step++)
     {
         // get new position
         CalculateNewPosition(pos, dir, index);
         distance += m_StepSize;
         tractLength +=  m_StepSize;
         distanceInVoxel += m_StepSize;
 
         // is new position valid (inside image, above FA threshold etc.)
         if (!IsValidPosition(pos, index, interpWeights, imageIdx))   // if not add last point and end streamline
         {
             m_SeedImage->TransformContinuousIndexToPhysicalPoint( pos, worldPos );
             ids.push_back(points->InsertNextPoint(worldPos.GetDataPointer()));
             return tractLength;
         }
         else if (distance>=m_PointPistance)
         {
             m_SeedImage->TransformContinuousIndexToPhysicalPoint( pos, worldPos );
             ids.push_back(points->InsertNextPoint(worldPos.GetDataPointer()));
             distance = 0;
         }
 
         if (!m_Interpolate)                         // use nearest neighbour interpolation
         {
             if (indexOld!=index)                    // did we enter a new voxel? if yes, calculate new direction
             {
                 double minAngle = 0;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     vnl_vector_fixed<double,3> newDir = m_PdImage.at(img)->GetPixel(index);   // get principal direction
                     if (newDir.magnitude()<mitk::eps)
                         continue;
 
                     typename InputImageType::PixelType tensor = m_InputImage.at(img)->GetPixel(index);
                     float scale = m_EmaxImage.at(img)->GetPixel(index);
                     newDir[0] = m_F*newDir[0] + (1-m_F)*( (1-m_G)*dirOld[0] + scale*m_G*(tensor[0]*dirOld[0] + tensor[1]*dirOld[1] + tensor[2]*dirOld[2]));
                     newDir[1] = m_F*newDir[1] + (1-m_F)*( (1-m_G)*dirOld[1] + scale*m_G*(tensor[1]*dirOld[0] + tensor[3]*dirOld[1] + tensor[4]*dirOld[2]));
                     newDir[2] = m_F*newDir[2] + (1-m_F)*( (1-m_G)*dirOld[2] + scale*m_G*(tensor[2]*dirOld[0] + tensor[4]*dirOld[1] + tensor[5]*dirOld[2]));
                     newDir.normalize();
 
                     float angle = dot_product(dirOld, newDir);
                     if (angle<0)
                     {
                         newDir *= -1;
                         angle *= -1;
                     }
 
                     if (angle>minAngle)
                     {
                         minAngle = angle;
                         dir = newDir;
                     }
                 }
 
                 //float r = m_StepSize/(2*std::asin(std::acos(minAngle)/2));
                 vnl_vector_fixed<double,3> v3 = dir+dirOld; v3 *= m_StepSize;
                 float a = m_StepSize;
                 float b = m_StepSize;
                 float c = v3.magnitude();
                 float r = a*b*c/std::sqrt((a+b+c)*(a+b-c)*(b+c-a)*(a-b+c)); // radius of triangle via Heron's formula (area of triangle)
 
                 if (r<m_MinCurvatureRadius)
                 {
                     return tractLength;
                 }
                 dirOld = dir;
                 indexOld = index;
                 distanceInVoxel = 0;
             }
             else
                 dir = dirOld;
         }
         else // use trilinear interpolation (weights calculated in IsValidPosition())
         {
             typename InputImageType::PixelType tensor;
 
             typename InputImageType::IndexType tmpIdx = index;
             typename InputImageType::PixelType tmpTensor;
 
             if (m_NumberOfInputs>1)
             {
                 double minAngle = 0;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     float angle = dot_product(dirOld, m_PdImage.at(img)->GetPixel(tmpIdx));
                     if (fabs(angle)>minAngle)
                     {
                         minAngle = angle;
                         tmpTensor = m_InputImage.at(img)->GetPixel(tmpIdx);
                     }
                 }
                 tensor = tmpTensor * interpWeights[0];
 
                 minAngle = 0;
                 tmpIdx = index; tmpIdx[0]++;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     float angle = dot_product(dirOld, m_PdImage.at(img)->GetPixel(tmpIdx));
                     if (fabs(angle)>minAngle)
                     {
                         minAngle = angle;
                         tmpTensor = m_InputImage.at(img)->GetPixel(tmpIdx);
                     }
                 }
                 tensor += tmpTensor * interpWeights[1];
 
                 minAngle = 0;
                 tmpIdx = index; tmpIdx[1]++;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     float angle = dot_product(dirOld, m_PdImage.at(img)->GetPixel(tmpIdx));
                     if (fabs(angle)>minAngle)
                     {
                         minAngle = angle;
                         tmpTensor = m_InputImage.at(img)->GetPixel(tmpIdx);
                     }
                 }
                 tensor += tmpTensor * interpWeights[2];
 
                 minAngle = 0;
                 tmpIdx = index; tmpIdx[2]++;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     float angle = dot_product(dirOld, m_PdImage.at(img)->GetPixel(tmpIdx));
                     if (fabs(angle)>minAngle)
                     {
                         minAngle = angle;
                         tmpTensor = m_InputImage.at(img)->GetPixel(tmpIdx);
                     }
                 }
                 tensor += tmpTensor * interpWeights[3];
 
                 minAngle = 0;
                 tmpIdx = index; tmpIdx[0]++; tmpIdx[1]++;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     float angle = dot_product(dirOld, m_PdImage.at(img)->GetPixel(tmpIdx));
                     if (fabs(angle)>minAngle)
                     {
                         minAngle = angle;
                         tmpTensor = m_InputImage.at(img)->GetPixel(tmpIdx);
                     }
                 }
                 tensor += tmpTensor * interpWeights[4];
 
                 minAngle = 0;
                 tmpIdx = index; tmpIdx[1]++; tmpIdx[2]++;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     float angle = dot_product(dirOld, m_PdImage.at(img)->GetPixel(tmpIdx));
                     if (fabs(angle)>minAngle)
                     {
                         minAngle = angle;
                         tmpTensor = m_InputImage.at(img)->GetPixel(tmpIdx);
                     }
                 }
                 tensor += tmpTensor * interpWeights[5];
 
                 minAngle = 0;
                 tmpIdx = index; tmpIdx[2]++; tmpIdx[0]++;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     float angle = dot_product(dirOld, m_PdImage.at(img)->GetPixel(tmpIdx));
                     if (fabs(angle)>minAngle)
                     {
                         minAngle = angle;
                         tmpTensor = m_InputImage.at(img)->GetPixel(tmpIdx);
                     }
                 }
                 tensor += tmpTensor * interpWeights[6];
 
                 minAngle = 0;
                 tmpIdx = index; tmpIdx[0]++; tmpIdx[1]++; tmpIdx[2]++;
                 for (int img=0; img<m_NumberOfInputs; img++)
                 {
                     float angle = dot_product(dirOld, m_PdImage.at(img)->GetPixel(tmpIdx));
                     if (fabs(angle)>minAngle)
                     {
                         minAngle = angle;
                         tmpTensor = m_InputImage.at(img)->GetPixel(tmpIdx);
                     }
                 }
                 tensor += tmpTensor * interpWeights[7];
             }
             else
             {
                 tensor = m_InputImage.at(0)->GetPixel(index) * interpWeights[0];
                 typename InputImageType::IndexType tmpIdx = index; tmpIdx[0]++;
                 tensor +=  m_InputImage.at(0)->GetPixel(tmpIdx) * interpWeights[1];
                 tmpIdx = index; tmpIdx[1]++;
                 tensor +=  m_InputImage.at(0)->GetPixel(tmpIdx) * interpWeights[2];
                 tmpIdx = index; tmpIdx[2]++;
                 tensor +=  m_InputImage.at(0)->GetPixel(tmpIdx) * interpWeights[3];
                 tmpIdx = index; tmpIdx[0]++; tmpIdx[1]++;
                 tensor +=  m_InputImage.at(0)->GetPixel(tmpIdx) * interpWeights[4];
                 tmpIdx = index; tmpIdx[1]++; tmpIdx[2]++;
                 tensor +=  m_InputImage.at(0)->GetPixel(tmpIdx) * interpWeights[5];
                 tmpIdx = index; tmpIdx[2]++; tmpIdx[0]++;
                 tensor +=  m_InputImage.at(0)->GetPixel(tmpIdx) * interpWeights[6];
                 tmpIdx = index; tmpIdx[0]++; tmpIdx[1]++; tmpIdx[2]++;
                 tensor +=  m_InputImage.at(0)->GetPixel(tmpIdx) * interpWeights[7];
             }
 
             tensor.ComputeEigenAnalysis(eigenvalues, eigenvectors);
             dir[0] = eigenvectors(2, 0);
             dir[1] = eigenvectors(2, 1);
             dir[2] = eigenvectors(2, 2);
             if (dir.magnitude()<mitk::eps)
                 continue;
             dir.normalize();
 
             float scale = 2/eigenvalues[2];
             dir[0] = m_F*dir[0] + (1-m_F)*( (1-m_G)*dirOld[0] + scale*m_G*(tensor[0]*dirOld[0] + tensor[1]*dirOld[1] + tensor[2]*dirOld[2]));
             dir[1] = m_F*dir[1] + (1-m_F)*( (1-m_G)*dirOld[1] + scale*m_G*(tensor[1]*dirOld[0] + tensor[3]*dirOld[1] + tensor[4]*dirOld[2]));
             dir[2] = m_F*dir[2] + (1-m_F)*( (1-m_G)*dirOld[2] + scale*m_G*(tensor[2]*dirOld[0] + tensor[4]*dirOld[1] + tensor[5]*dirOld[2]));
             dir.normalize();
 
             float angle = dot_product(dirOld, dir);
             if (angle<0)
             {
                 dir *= -1;
                 angle *= -1;
             }
 
             vnl_vector_fixed<double,3> v3 = dir+dirOld; v3 *= m_StepSize;
             float a = m_StepSize;
             float b = m_StepSize;
             float c = v3.magnitude();
             float r = a*b*c/std::sqrt((a+b+c)*(a+b-c)*(b+c-a)*(a-b+c)); // radius of triangle via Heron's formula (area of triangle)
 
             if (r<m_MinCurvatureRadius)
                 return tractLength;
 
             dirOld = dir;
             indexOld = index;
         }
     }
     return tractLength;
 }
 
 template< class TTensorPixelType,
           class TPDPixelType>
 void StreamlineTrackingFilter< TTensorPixelType,
 TPDPixelType>
 ::ThreadedGenerateData(const OutputImageRegionType& outputRegionForThread,
                        ThreadIdType threadId)
 {
     FiberPolyDataType poly = m_PolyDataContainer->GetElement(threadId);
     vtkSmartPointer<vtkPoints> points = vtkSmartPointer<vtkPoints>::New();
     vtkSmartPointer<vtkCellArray> Cells = vtkSmartPointer<vtkCellArray>::New();
 
     typedef itk::DiffusionTensor3D<TTensorPixelType>        TensorType;
     typedef ImageRegionConstIterator< InputImageType >      InputIteratorType;
     typedef ImageRegionConstIterator< ItkUcharImgType >     MaskIteratorType;
     typedef ImageRegionConstIterator< ItkFloatImgType >     FloatIteratorType;
     typedef typename InputImageType::PixelType              InputTensorType;
 
     MaskIteratorType    sit(m_SeedImage, outputRegionForThread );
     FloatIteratorType   fit(m_FaImage, outputRegionForThread );
     MaskIteratorType    mit(m_MaskImage, outputRegionForThread );
 
     for (int img=0; img<m_NumberOfInputs; img++)
     {
         sit.GoToBegin();
         mit.GoToBegin();
         fit.GoToBegin();
         itk::Point<double> worldPos;
         while( !sit.IsAtEnd() )
         {
             if (sit.Value()==0 || fit.Value()<m_FaThreshold || mit.Value()==0)
             {
                 ++sit;
                 ++mit;
                 ++fit;
                 continue;
             }
 
             for (int s=0; s<m_SeedsPerVoxel; s++)
             {
                 vtkSmartPointer<vtkPolyLine> line = vtkSmartPointer<vtkPolyLine>::New();
                 std::vector< vtkIdType > pointIDs;
                 typename InputImageType::IndexType index = sit.GetIndex();
                 itk::ContinuousIndex<double, 3> start;
                 unsigned int counter = 0;
 
                 if (m_SeedsPerVoxel>1)
                 {
                     start[0] = index[0]+(double)(rand()%99-49)/100;
                     start[1] = index[1]+(double)(rand()%99-49)/100;
                     start[2] = index[2]+(double)(rand()%99-49)/100;
                 }
                 else
                 {
                     start[0] = index[0];
                     start[1] = index[1];
                     start[2] = index[2];
                 }
 
                 // forward tracking
                 float tractLength = FollowStreamline(start, 1, points, pointIDs, img);
 
                 // add ids to line
                 counter += pointIDs.size();
                 while (!pointIDs.empty())
                 {
                     line->GetPointIds()->InsertNextId(pointIDs.back());
                     pointIDs.pop_back();
                 }
 
                 // insert start point
                 m_SeedImage->TransformContinuousIndexToPhysicalPoint( start, worldPos );
                 line->GetPointIds()->InsertNextId(points->InsertNextPoint(worldPos.GetDataPointer()));
 
                 // backward tracking
                 tractLength += FollowStreamline(start, -1, points, pointIDs, img);
 
                 counter += pointIDs.size();
 
                 //MITK_INFO << "Tract length " << tractLength;
 
                 if (tractLength<m_MinTractLength || counter<2)
                     continue;
 
                 // add ids to line
                 for (unsigned int i=0; i<pointIDs.size(); i++)
                     line->GetPointIds()->InsertNextId(pointIDs.at(i));
 
                 Cells->InsertNextCell(line);
             }
             ++sit;
             ++mit;
             ++fit;
         }
     }
     poly->SetPoints(points);
     poly->SetLines(Cells);
 
     std::cout << "Thread " << threadId << " finished tracking" << std::endl;
 }
 
 template< class TTensorPixelType,
           class TPDPixelType>
 vtkSmartPointer< vtkPolyData > StreamlineTrackingFilter< TTensorPixelType,
 TPDPixelType>
 ::AddPolyData(FiberPolyDataType poly1, FiberPolyDataType poly2)
 {
     vtkSmartPointer<vtkPolyData> vNewPolyData = vtkSmartPointer<vtkPolyData>::New();
     vtkSmartPointer<vtkCellArray> vNewLines = poly1->GetLines();
     vtkSmartPointer<vtkPoints> vNewPoints = poly1->GetPoints();
 
     for( int i=0; i<poly2->GetNumberOfLines(); i++ )
     {
         vtkCell* cell = poly2->GetCell(i);
         int numPoints = cell->GetNumberOfPoints();
         vtkPoints* points = cell->GetPoints();
 
         vtkSmartPointer<vtkPolyLine> container = vtkSmartPointer<vtkPolyLine>::New();
         for (int j=0; j<numPoints; j++)
         {
             double p[3];
             points->GetPoint(j, p);
 
             vtkIdType id = vNewPoints->InsertNextPoint(p);
             container->GetPointIds()->InsertNextId(id);
         }
         vNewLines->InsertNextCell(container);
     }
 
     // initialize polydata
     vNewPolyData->SetPoints(vNewPoints);
     vNewPolyData->SetLines(vNewLines);
 
     return vNewPolyData;
 }
 template< class TTensorPixelType,
           class TPDPixelType>
 void StreamlineTrackingFilter< TTensorPixelType,
 TPDPixelType>
 ::AfterThreadedGenerateData()
 {
     MITK_INFO << "Generating polydata ";
     m_FiberPolyData = m_PolyDataContainer->GetElement(0);
     for (unsigned int i=1; i<this->GetNumberOfThreads(); i++)
     {
         m_FiberPolyData = AddPolyData(m_FiberPolyData, m_PolyDataContainer->GetElement(i));
     }
     MITK_INFO << "done";
 }
 
 template< class TTensorPixelType,
           class TPDPixelType>
 void StreamlineTrackingFilter< TTensorPixelType,
 TPDPixelType>
 ::PrintSelf(std::ostream& os, Indent indent) const
 {
 }
 
 }
 #endif // __itkDiffusionQballPrincipleDirectionsImageFilter_txx
diff --git a/Modules/DiffusionImaging/FiberTracking/Testing/CMakeLists.txt b/Modules/DiffusionImaging/FiberTracking/Testing/CMakeLists.txt
index 2050e47d81..f5a6692d8d 100644
--- a/Modules/DiffusionImaging/FiberTracking/Testing/CMakeLists.txt
+++ b/Modules/DiffusionImaging/FiberTracking/Testing/CMakeLists.txt
@@ -1,11 +1,11 @@
 MITK_CREATE_MODULE_TESTS()
 
 mitkAddCustomModuleTest(mitkFiberBundleXReaderWriterTest mitkFiberBundleXReaderWriterTest ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX.fib)
 mitkAddCustomModuleTest(mitkGibbsTrackingTest mitkGibbsTrackingTest ${MITK_DATA_DIR}/DiffusionImaging/qBallImage.qbi ${MITK_DATA_DIR}/DiffusionImaging/diffusionImageMask.nrrd ${MITK_DATA_DIR}/DiffusionImaging/gibbsTrackingParameters.gtp ${MITK_DATA_DIR}/DiffusionImaging/gibbsTractogram.fib)
-mitkAddCustomModuleTest(mitkStreamlineTrackingTest mitkStreamlineTrackingTest ${MITK_DATA_DIR}/DiffusionImaging/tensorImage.dti ${MITK_DATA_DIR}/DiffusionImaging/diffusionImageMask.nrrd ${MITK_DATA_DIR}/DiffusionImaging/streamlineTractogram.fib)
+mitkAddCustomModuleTest(mitkStreamlineTrackingTest mitkStreamlineTrackingTest ${MITK_DATA_DIR}/DiffusionImaging/tensorImage.dti ${MITK_DATA_DIR}/DiffusionImaging/diffusionImageMask.nrrd ${MITK_DATA_DIR}/DiffusionImaging/streamlineTractogramInterpolated.fib)
 #mitkAddCustomModuleTest(mitkPeakExtractionTest mitkPeakExtractionTest ${MITK_DATA_DIR}/DiffusionImaging/qBallImage_SHCoeffs.nrrd ${MITK_DATA_DIR}/DiffusionImaging/diffusionImageMask.nrrd ${MITK_DATA_DIR}/DiffusionImaging/qBallImage_VectorField.fib)
 mitkAddCustomModuleTest(mitkLocalFiberPlausibilityTest mitkLocalFiberPlausibilityTest ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX.fib ${MITK_DATA_DIR}/DiffusionImaging/LDFP_GT_DIRECTION_0.nrrd ${MITK_DATA_DIR}/DiffusionImaging/LDFP_GT_DIRECTION_1.nrrd ${MITK_DATA_DIR}/DiffusionImaging/LDFP_ERROR_IMAGE.nrrd ${MITK_DATA_DIR}/DiffusionImaging/LDFP_NUM_DIRECTIONS.nrrd ${MITK_DATA_DIR}/DiffusionImaging/LDFP_VECTOR_FIELD.fib ${MITK_DATA_DIR}/DiffusionImaging/LDFP_ERROR_IMAGE_IGNORE.nrrd)
 mitkAddCustomModuleTest(mitkFiberTransformationTest mitkFiberTransformationTest ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX.fib ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX_transformed.fib)
 mitkAddCustomModuleTest(mitkFiberExtractionTest mitkFiberExtractionTest ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX.fib ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX_extracted.fib ${MITK_DATA_DIR}/DiffusionImaging/ROI1.pf ${MITK_DATA_DIR}/DiffusionImaging/ROI2.pf ${MITK_DATA_DIR}/DiffusionImaging/ROI3.pf ${MITK_DATA_DIR}/DiffusionImaging/ROIIMAGE.nrrd ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX_inside.fib ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX_outside.fib ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX_passing-mask.fib ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX_ending-in-mask.fib ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX_subtracted.fib ${MITK_DATA_DIR}/DiffusionImaging/fiberBundleX_added.fib)
 mitkAddCustomModuleTest(mitkFiberGenerationTest mitkFiberGenerationTest ${MITK_DATA_DIR}/DiffusionImaging/Fiberfox/Fiducial_0.pf ${MITK_DATA_DIR}/DiffusionImaging/Fiberfox/Fiducial_1.pf ${MITK_DATA_DIR}/DiffusionImaging/Fiberfox/Fiducial_2.pf ${MITK_DATA_DIR}/DiffusionImaging/Fiberfox/uniform.fib ${MITK_DATA_DIR}/DiffusionImaging/Fiberfox/gaussian.fib)
 # TODO: fiberfox signalgen
diff --git a/Modules/DiffusionImaging/FiberTracking/Testing/mitkStreamlineTrackingTest.cpp b/Modules/DiffusionImaging/FiberTracking/Testing/mitkStreamlineTrackingTest.cpp
index ade4aa983d..6ed17969da 100755
--- a/Modules/DiffusionImaging/FiberTracking/Testing/mitkStreamlineTrackingTest.cpp
+++ b/Modules/DiffusionImaging/FiberTracking/Testing/mitkStreamlineTrackingTest.cpp
@@ -1,130 +1,135 @@
 /*===================================================================
 
 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 <mitkImageCast.h>
 #include <mitkTensorImage.h>
 #include <mitkIOUtil.h>
 #include <mitkBaseDataIOFactory.h>
 #include <mitkDiffusionCoreObjectFactory.h>
 #include <mitkFiberTrackingObjectFactory.h>
 #include <mitkFiberBundleX.h>
 #include <itkStreamlineTrackingFilter.h>
 #include <itkDiffusionTensor3D.h>
 #include <mitkTestingMacros.h>
 
 using namespace std;
 
 int mitkStreamlineTrackingTest(int argc, char* argv[])
 {
     MITK_TEST_BEGIN("mitkStreamlineTrackingTest");
 
     MITK_TEST_CONDITION_REQUIRED(argc>3,"check for input data")
 
     string dtiFileName = argv[1];
     string maskFileName = argv[2];
     string referenceFileName = argv[3];
 
     MITK_INFO << "DTI file: " << dtiFileName;
     MITK_INFO << "Mask file: " << maskFileName;
     MITK_INFO << "Reference fiber file: " << referenceFileName;
 
     float minFA = 0.05;
     float minCurv = -1;
     float stepSize = -1;
     float tendf = 1;
     float tendg = 0;
     float minLength = 20;
     int numSeeds = 1;
-    bool interpolate = false;
+    bool interpolate = true;
 
     try
     {
         RegisterDiffusionCoreObjectFactory();
         RegisterFiberTrackingObjectFactory();
 
         // load input image
         const std::string s1="", s2="";
         std::vector<mitk::BaseData::Pointer> infile = mitk::BaseDataIO::LoadBaseDataFromFile( dtiFileName, s1, s2, false );
 
         MITK_INFO << "Loading tensor image ...";
         typedef itk::Image< itk::DiffusionTensor3D<float>, 3 >    ItkTensorImage;
         mitk::TensorImage::Pointer mitkTensorImage = dynamic_cast<mitk::TensorImage*>(infile.at(0).GetPointer());
         ItkTensorImage::Pointer itk_dti = ItkTensorImage::New();
         mitk::CastToItkImage<ItkTensorImage>(mitkTensorImage, itk_dti);
 
         MITK_INFO << "Loading seed image ...";
         typedef itk::Image< unsigned char, 3 >    ItkUCharImageType;
         mitk::Image::Pointer mitkSeedImage = mitk::IOUtil::LoadImage(maskFileName);
 
         MITK_INFO << "Loading mask image ...";
         mitk::Image::Pointer mitkMaskImage = mitk::IOUtil::LoadImage(maskFileName);
 
         // instantiate tracker
         typedef itk::StreamlineTrackingFilter< float > FilterType;
         FilterType::Pointer filter = FilterType::New();
         filter->SetInput(itk_dti);
         filter->SetSeedsPerVoxel(numSeeds);
         filter->SetFaThreshold(minFA);
         filter->SetMinCurvatureRadius(minCurv);
         filter->SetStepSize(stepSize);
         filter->SetF(tendf);
         filter->SetG(tendg);
         filter->SetInterpolate(interpolate);
         filter->SetMinTractLength(minLength);
         filter->SetNumberOfThreads(1);
 
         if (mitkSeedImage.IsNotNull())
         {
             ItkUCharImageType::Pointer mask = ItkUCharImageType::New();
             mitk::CastToItkImage<ItkUCharImageType>(mitkSeedImage, mask);
             filter->SetSeedImage(mask);
         }
 
         if (mitkMaskImage.IsNotNull())
         {
             ItkUCharImageType::Pointer mask = ItkUCharImageType::New();
             mitk::CastToItkImage<ItkUCharImageType>(mitkMaskImage, mask);
             filter->SetMaskImage(mask);
         }
 
         filter->Update();
 
         vtkSmartPointer<vtkPolyData> fiberBundle = filter->GetFiberPolyData();
         mitk::FiberBundleX::Pointer fib1 = mitk::FiberBundleX::New(fiberBundle);
 
+        mitk::FiberBundleXWriter::Pointer writer = mitk::FiberBundleXWriter::New();
+        writer->SetFileName("testBundle.fib");
+        writer->SetInputFiberBundleX(fib1);
+        writer->Update();
+
         infile = mitk::BaseDataIO::LoadBaseDataFromFile( referenceFileName, s1, s2, false );
         mitk::FiberBundleX::Pointer fib2 = dynamic_cast<mitk::FiberBundleX*>(infile.at(0).GetPointer());
         MITK_TEST_CONDITION_REQUIRED(fib2.IsNotNull(), "Check if reference tractogram is not null.");
         MITK_TEST_CONDITION_REQUIRED(fib1->Equals(fib2), "Check if tractograms are equal.");
     }
     catch (itk::ExceptionObject e)
     {
         MITK_INFO << e;
         return EXIT_FAILURE;
     }
     catch (std::exception e)
     {
         MITK_INFO << e.what();
         return EXIT_FAILURE;
     }
     catch (...)
     {
         MITK_INFO << "ERROR!?!";
         return EXIT_FAILURE;
     }
 
     MITK_TEST_END();
 }