diff --git a/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.cpp b/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.cpp
index 022fa7e40f..b5f3974b19 100755
--- a/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.cpp
+++ b/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.cpp
@@ -1,711 +1,711 @@
 /*===================================================================
 
 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 "itkTractsToDWIImageFilter.h"
 #include <boost/progress.hpp>
 #include <vtkSmartPointer.h>
 #include <vtkPolyData.h>
 #include <vtkCellArray.h>
 #include <vtkPoints.h>
 #include <vtkPolyLine.h>
 #include <itkImageRegionIteratorWithIndex.h>
 #include <itkResampleImageFilter.h>
 #include <itkNearestNeighborInterpolateImageFunction.h>
 #include <itkBSplineInterpolateImageFunction.h>
 #include <itkCastImageFilter.h>
 #include <itkImageFileWriter.h>
 #include <itkRescaleIntensityImageFilter.h>
 #include <itkWindowedSincInterpolateImageFunction.h>
 #include <itkResampleDwiImageFilter.h>
 #include <itkKspaceImageFilter.h>
 #include <itkDftImageFilter.h>
 #include <itkAddImageFilter.h>
 
 namespace itk
 {
 
 template< class PixelType >
 TractsToDWIImageFilter< PixelType >::TractsToDWIImageFilter()
     : m_CircleDummy(false)
     , m_VolumeAccuracy(10)
     , m_Upsampling(1)
     , m_NumberOfRepetitions(1)
     , m_EnforcePureFiberVoxels(false)
     , m_InterpolationShrink(1000)
     , m_FiberRadius(0)
     , m_SignalScale(25)
     , m_kOffset(0)
     , m_tLine(1)
     , m_UseInterpolation(false)
     , m_SimulateRelaxation(true)
     , m_tInhom(50)
     , m_TE(100)
     , m_FrequencyMap(NULL)
     , m_EddyGradientStrength(0.001)
     , m_SimulateEddyCurrents(false)
 {
     m_Spacing.Fill(2.5); m_Origin.Fill(0.0);
     m_DirectionMatrix.SetIdentity();
     m_ImageRegion.SetSize(0, 10);
     m_ImageRegion.SetSize(1, 10);
     m_ImageRegion.SetSize(2, 10);
 }
 
 template< class PixelType >
 TractsToDWIImageFilter< PixelType >::~TractsToDWIImageFilter()
 {
 
 }
 
 template< class PixelType >
 TractsToDWIImageFilter< PixelType >::DoubleDwiType::Pointer TractsToDWIImageFilter< PixelType >::DoKspaceStuff( std::vector< DoubleDwiType::Pointer >& images )
 {
     // create slice object
     ImageRegion<2> sliceRegion;
     sliceRegion.SetSize(0, m_UpsampledImageRegion.GetSize()[0]);
     sliceRegion.SetSize(1, m_UpsampledImageRegion.GetSize()[1]);
     Vector< double, 2 > sliceSpacing;
     sliceSpacing[0] = m_UpsampledSpacing[0];
     sliceSpacing[1] = m_UpsampledSpacing[1];
 
     // frequency map slice
     SliceType::Pointer fMap = NULL;
     if (m_FrequencyMap.IsNotNull())
     {
         fMap = SliceType::New();
         ImageRegion<2> region;
         region.SetSize(0, m_UpsampledImageRegion.GetSize()[0]);
         region.SetSize(1, m_UpsampledImageRegion.GetSize()[1]);
         fMap->SetLargestPossibleRegion( region );
         fMap->SetBufferedRegion( region );
         fMap->SetRequestedRegion( region );
         fMap->Allocate();
     }
 
     DoubleDwiType::Pointer newImage = DoubleDwiType::New();
     newImage->SetSpacing( m_Spacing );
     newImage->SetOrigin( m_Origin );
     newImage->SetDirection( m_DirectionMatrix );
     newImage->SetLargestPossibleRegion( m_ImageRegion );
     newImage->SetBufferedRegion( m_ImageRegion );
     newImage->SetRequestedRegion( m_ImageRegion );
     newImage->SetVectorLength( images.at(0)->GetVectorLength() );
     newImage->Allocate();
 
     MatrixType transform = m_DirectionMatrix;
     for (int i=0; i<3; i++)
         for (int j=0; j<3; j++)
         {
             if (j<2)
                 transform[i][j] *= m_UpsampledSpacing[j];
             else
                 transform[i][j] *= m_Spacing[j];
         }
 
     boost::progress_display disp(images.at(0)->GetVectorLength()*images.at(0)->GetLargestPossibleRegion().GetSize(2));
     for (int g=0; g<images.at(0)->GetVectorLength(); g++)
         for (int z=0; z<images.at(0)->GetLargestPossibleRegion().GetSize(2); z++)
         {
             std::vector< SliceType::Pointer > compartmentSlices;
             std::vector< double > t2Vector;
 
             for (int i=0; i<images.size(); i++)
             {
                 DiffusionSignalModel<double>* signalModel;
                 if (i<m_FiberModels.size())
                     signalModel = m_FiberModels.at(i);
                 else
                     signalModel = m_NonFiberModels.at(i-m_FiberModels.size());
 
                 SliceType::Pointer slice = SliceType::New();
                 slice->SetLargestPossibleRegion( sliceRegion );
                 slice->SetBufferedRegion( sliceRegion );
                 slice->SetRequestedRegion( sliceRegion );
                 slice->SetSpacing(sliceSpacing);
                 slice->Allocate();
                 slice->FillBuffer(0.0);
 
                 // extract slice from channel g
                 for (int y=0; y<images.at(0)->GetLargestPossibleRegion().GetSize(1); y++)
                     for (int x=0; x<images.at(0)->GetLargestPossibleRegion().GetSize(0); x++)
                     {
                         SliceType::IndexType index2D; index2D[0]=x; index2D[1]=y;
                         DoubleDwiType::IndexType index3D; index3D[0]=x; index3D[1]=y; index3D[2]=z;
 
                         slice->SetPixel(index2D, images.at(i)->GetPixel(index3D)[g]);
 
                         if (fMap.IsNotNull() && i==0)
                             fMap->SetPixel(index2D, m_FrequencyMap->GetPixel(index3D));
                     }
 
                 compartmentSlices.push_back(slice);
                 t2Vector.push_back(signalModel->GetT2());
             }
 
             // create k-sapce (inverse fourier transform slices)
             itk::Size<2> outSize; outSize.SetElement(0, m_ImageRegion.GetSize(0)); outSize.SetElement(1, m_ImageRegion.GetSize(1));
             itk::KspaceImageFilter< SliceType::PixelType >::Pointer idft = itk::KspaceImageFilter< SliceType::PixelType >::New();
             idft->SetCompartmentImages(compartmentSlices);
             idft->SetT2(t2Vector);
             idft->SetkOffset(m_kOffset);
             idft->SettLine(m_tLine);
             idft->SetTE(m_TE);
             idft->SetTinhom(m_tInhom);
             idft->SetSimulateRelaxation(m_SimulateRelaxation);
             idft->SetSimulateEddyCurrents(m_SimulateEddyCurrents);
             idft->SetEddyGradientMagnitude(m_EddyGradientStrength);
             idft->SetZ((double)z-(double)images.at(0)->GetLargestPossibleRegion().GetSize(2)/2.0);
             idft->SetDirectionMatrix(transform);
             idft->SetDiffusionGradientDirection(m_FiberModels.at(0)->GetGradientDirection(g));
             idft->SetFrequencyMap(fMap);
             idft->SetSignalScale(m_SignalScale);
             idft->SetOutSize(outSize);
             idft->Update();
 
             ComplexSliceType::Pointer fSlice;
             fSlice = idft->GetOutput();
 
             for (int i=0; i<m_KspaceArtifacts.size(); i++)
                 fSlice = m_KspaceArtifacts.at(i)->AddArtifact(fSlice);
 
             // fourier transform slice
             SliceType::Pointer newSlice;
             itk::DftImageFilter< SliceType::PixelType >::Pointer dft = itk::DftImageFilter< SliceType::PixelType >::New();
             dft->SetInput(fSlice);
             dft->Update();
             newSlice = dft->GetOutput();
 
             // put slice back into channel g
             for (int y=0; y<fSlice->GetLargestPossibleRegion().GetSize(1); y++)
                 for (int x=0; x<fSlice->GetLargestPossibleRegion().GetSize(0); x++)
                 {
                     DoubleDwiType::IndexType index3D; index3D[0]=x; index3D[1]=y; index3D[2]=z;
                     SliceType::IndexType index2D; index2D[0]=x; index2D[1]=y;
 
                     DoubleDwiType::PixelType pix3D = newImage->GetPixel(index3D);
                     pix3D[g] = newSlice->GetPixel(index2D);
                     newImage->SetPixel(index3D, pix3D);
                 }
 
             ++disp;
         }
     return newImage;
 }
 
-template< class PixelType >
-TractsToDWIImageFilter< PixelType >::ComplexSliceType::Pointer TractsToDWIImageFilter< PixelType >::RearrangeSlice(ComplexSliceType::Pointer slice)
-{
-    ImageRegion<2> region = slice->GetLargestPossibleRegion();
-    ComplexSliceType::Pointer rearrangedSlice = ComplexSliceType::New();
-    rearrangedSlice->SetLargestPossibleRegion( region );
-    rearrangedSlice->SetBufferedRegion( region );
-    rearrangedSlice->SetRequestedRegion( region );
-    rearrangedSlice->Allocate();
-
-    int xHalf = region.GetSize(0)/2;
-    int yHalf = region.GetSize(1)/2;
-
-    for (int y=0; y<region.GetSize(1); y++)
-        for (int x=0; x<region.GetSize(0); x++)
-        {
-            SliceType::IndexType idx;
-            idx[0]=x; idx[1]=y;
-            vcl_complex< double > pix = slice->GetPixel(idx);
-
-            if( idx[0] <  xHalf )
-                idx[0] = idx[0] + xHalf;
-            else
-                idx[0] = idx[0] - xHalf;
-
-            if( idx[1] <  yHalf )
-                idx[1] = idx[1] + yHalf;
-            else
-                idx[1] = idx[1] - yHalf;
-
-            rearrangedSlice->SetPixel(idx, pix);
-        }
-
-    return rearrangedSlice;
-}
+//template< class PixelType >
+//TractsToDWIImageFilter< PixelType >::ComplexSliceType::Pointer TractsToDWIImageFilter< PixelType >::RearrangeSlice(ComplexSliceType::Pointer slice)
+//{
+//    ImageRegion<2> region = slice->GetLargestPossibleRegion();
+//    ComplexSliceType::Pointer rearrangedSlice = ComplexSliceType::New();
+//    rearrangedSlice->SetLargestPossibleRegion( region );
+//    rearrangedSlice->SetBufferedRegion( region );
+//    rearrangedSlice->SetRequestedRegion( region );
+//    rearrangedSlice->Allocate();
+
+//    int xHalf = region.GetSize(0)/2;
+//    int yHalf = region.GetSize(1)/2;
+
+//    for (int y=0; y<region.GetSize(1); y++)
+//        for (int x=0; x<region.GetSize(0); x++)
+//        {
+//            SliceType::IndexType idx;
+//            idx[0]=x; idx[1]=y;
+//            vcl_complex< double > pix = slice->GetPixel(idx);
+
+//            if( idx[0] <  xHalf )
+//                idx[0] = idx[0] + xHalf;
+//            else
+//                idx[0] = idx[0] - xHalf;
+
+//            if( idx[1] <  yHalf )
+//                idx[1] = idx[1] + yHalf;
+//            else
+//                idx[1] = idx[1] - yHalf;
+
+//            rearrangedSlice->SetPixel(idx, pix);
+//        }
+
+//    return rearrangedSlice;
+//}
 
 template< class PixelType >
 void TractsToDWIImageFilter< PixelType >::GenerateData()
 {
     // check input data
     if (m_FiberBundle.IsNull())
         itkExceptionMacro("Input fiber bundle is NULL!");
 
     int numFibers = m_FiberBundle->GetNumFibers();
     if (numFibers<=0)
         itkExceptionMacro("Input fiber bundle contains no fibers!");
 
     if (m_FiberModels.empty())
         itkExceptionMacro("No diffusion model for fiber compartments defined!");
 
     if (m_NonFiberModels.empty())
         itkExceptionMacro("No diffusion model for non-fiber compartments defined!");
 
     int baselineIndex = m_FiberModels[0]->GetFirstBaselineIndex();
     if (baselineIndex<0)
         itkExceptionMacro("No baseline index found!");
 
     // check k-space undersampling
     if (m_Upsampling<1)
         m_Upsampling = 1;
 
     if (m_TissueMask.IsNotNull())
     {
         // use input tissue mask
         m_Spacing = m_TissueMask->GetSpacing();
         m_Origin = m_TissueMask->GetOrigin();
         m_DirectionMatrix = m_TissueMask->GetDirection();
         m_ImageRegion = m_TissueMask->GetLargestPossibleRegion();
 
         if (m_Upsampling>1.00001)
         {
             MITK_INFO << "Adding ringing artifacts. Image upsampling factor: " << m_Upsampling;
             ImageRegion<3> region = m_ImageRegion;
             region.SetSize(0, m_ImageRegion.GetSize(0)*m_Upsampling);
             region.SetSize(1, m_ImageRegion.GetSize(1)*m_Upsampling);
             itk::Vector<double> spacing = m_Spacing;
             spacing[0] /= m_Upsampling;
             spacing[1] /= m_Upsampling;
             itk::RescaleIntensityImageFilter<ItkUcharImgType,ItkUcharImgType>::Pointer rescaler = itk::RescaleIntensityImageFilter<ItkUcharImgType,ItkUcharImgType>::New();
             rescaler->SetInput(0,m_TissueMask);
             rescaler->SetOutputMaximum(100);
             rescaler->SetOutputMinimum(0);
             rescaler->Update();
 
             itk::ResampleImageFilter<ItkUcharImgType, ItkUcharImgType>::Pointer resampler = itk::ResampleImageFilter<ItkUcharImgType, ItkUcharImgType>::New();
             resampler->SetInput(rescaler->GetOutput());
             resampler->SetOutputParametersFromImage(m_TissueMask);
             resampler->SetSize(region.GetSize());
             resampler->SetOutputSpacing(spacing);
             resampler->Update();
             m_TissueMask = resampler->GetOutput();
         }
         MITK_INFO << "Using tissue mask";
     }
 
     // initialize output dwi image
     typename OutputImageType::Pointer outImage = OutputImageType::New();
     outImage->SetSpacing( m_Spacing );
     outImage->SetOrigin( m_Origin );
     outImage->SetDirection( m_DirectionMatrix );
     outImage->SetLargestPossibleRegion( m_ImageRegion );
     outImage->SetBufferedRegion( m_ImageRegion );
     outImage->SetRequestedRegion( m_ImageRegion );
     outImage->SetVectorLength( m_FiberModels[0]->GetNumGradients() );
     outImage->Allocate();
     typename OutputImageType::PixelType temp;
     temp.SetSize(m_FiberModels[0]->GetNumGradients());
     temp.Fill(0.0);
     outImage->FillBuffer(temp);
 
     // is input slize size a power of two?
     int x=m_ImageRegion.GetSize(0); int y=m_ImageRegion.GetSize(1);
     if ( x%2 == 1 )
         x += 1;
     if ( y%2 == 1 )
         y += 1;
 
     // if not, adjust size and dimension (needed for FFT); zero-padding
     if (x!=m_ImageRegion.GetSize(0))
         m_ImageRegion.SetSize(0, x);
     if (y!=m_ImageRegion.GetSize(1))
         m_ImageRegion.SetSize(1, y);
 
     // apply undersampling to image parameters
     m_UpsampledSpacing = m_Spacing;
     m_UpsampledImageRegion = m_ImageRegion;
     m_UpsampledSpacing[0] /= m_Upsampling;
     m_UpsampledSpacing[1] /= m_Upsampling;
     m_UpsampledImageRegion.SetSize(0, m_ImageRegion.GetSize()[0]*m_Upsampling);
     m_UpsampledImageRegion.SetSize(1, m_ImageRegion.GetSize()[1]*m_Upsampling);
 
     // everything from here on is using the upsampled image parameters!!!
     if (m_TissueMask.IsNull())
     {
         m_TissueMask = ItkUcharImgType::New();
         m_TissueMask->SetSpacing( m_UpsampledSpacing );
         m_TissueMask->SetOrigin( m_Origin );
         m_TissueMask->SetDirection( m_DirectionMatrix );
         m_TissueMask->SetLargestPossibleRegion( m_UpsampledImageRegion );
         m_TissueMask->SetBufferedRegion( m_UpsampledImageRegion );
         m_TissueMask->SetRequestedRegion( m_UpsampledImageRegion );
         m_TissueMask->Allocate();
         m_TissueMask->FillBuffer(1);
     }
 
     // resample frequency map
     if (m_FrequencyMap.IsNotNull())
     {
         itk::ResampleImageFilter<ItkDoubleImgType, ItkDoubleImgType>::Pointer resampler = itk::ResampleImageFilter<ItkDoubleImgType, ItkDoubleImgType>::New();
         resampler->SetInput(m_FrequencyMap);
         resampler->SetOutputParametersFromImage(m_FrequencyMap);
         resampler->SetSize(m_UpsampledImageRegion.GetSize());
         resampler->SetOutputSpacing(m_UpsampledSpacing);
         resampler->Update();
         m_FrequencyMap = resampler->GetOutput();
     }
 
     // initialize volume fraction images
     m_VolumeFractions.clear();
     for (int i=0; i<m_FiberModels.size()+m_NonFiberModels.size(); i++)
     {
         ItkDoubleImgType::Pointer tempimg = ItkDoubleImgType::New();
         tempimg->SetSpacing( m_UpsampledSpacing );
         tempimg->SetOrigin( m_Origin );
         tempimg->SetDirection( m_DirectionMatrix );
         tempimg->SetLargestPossibleRegion( m_UpsampledImageRegion );
         tempimg->SetBufferedRegion( m_UpsampledImageRegion );
         tempimg->SetRequestedRegion( m_UpsampledImageRegion );
         tempimg->Allocate();
         tempimg->FillBuffer(0);
         m_VolumeFractions.push_back(tempimg);
     }
 
     // resample fiber bundle for sufficient voxel coverage
     double segmentVolume = 0.0001;
     float minSpacing = 1;
     if(m_UpsampledSpacing[0]<m_UpsampledSpacing[1] && m_UpsampledSpacing[0]<m_UpsampledSpacing[2])
         minSpacing = m_UpsampledSpacing[0];
     else if (m_UpsampledSpacing[1] < m_UpsampledSpacing[2])
         minSpacing = m_UpsampledSpacing[1];
     else
         minSpacing = m_UpsampledSpacing[2];
     FiberBundleType fiberBundle = m_FiberBundle->GetDeepCopy();
     fiberBundle->ResampleFibers(minSpacing/m_VolumeAccuracy);
     double mmRadius = m_FiberRadius/1000;
     if (mmRadius>0)
         segmentVolume = M_PI*mmRadius*mmRadius*minSpacing/m_VolumeAccuracy;
 
     // generate double images to work with because we don't want to lose precision
     // we use a separate image for each compartment model
     std::vector< DoubleDwiType::Pointer > compartments;
     for (int i=0; i<m_FiberModels.size()+m_NonFiberModels.size(); i++)
     {
         DoubleDwiType::Pointer doubleDwi = DoubleDwiType::New();
         doubleDwi->SetSpacing( m_UpsampledSpacing );
         doubleDwi->SetOrigin( m_Origin );
         doubleDwi->SetDirection( m_DirectionMatrix );
         doubleDwi->SetLargestPossibleRegion( m_UpsampledImageRegion );
         doubleDwi->SetBufferedRegion( m_UpsampledImageRegion );
         doubleDwi->SetRequestedRegion( m_UpsampledImageRegion );
         doubleDwi->SetVectorLength( m_FiberModels[0]->GetNumGradients() );
         doubleDwi->Allocate();
         DoubleDwiType::PixelType pix;
         pix.SetSize(m_FiberModels[0]->GetNumGradients());
         pix.Fill(0.0);
         doubleDwi->FillBuffer(pix);
         compartments.push_back(doubleDwi);
     }
 
     double interpFact = 2*atan(-0.5*m_InterpolationShrink);
     double maxVolume = 0;
 
     MITK_INFO << "Generating signal of " << m_FiberModels.size() << " fiber compartments";
     vtkSmartPointer<vtkPolyData> fiberPolyData = fiberBundle->GetFiberPolyData();
     boost::progress_display disp(numFibers);
     for( int i=0; i<numFibers; i++ )
     {
         vtkCell* cell = fiberPolyData->GetCell(i);
         int numPoints = cell->GetNumberOfPoints();
         vtkPoints* points = cell->GetPoints();
 
         if (numPoints<2)
             continue;
 
         for( int j=0; j<numPoints; j++)
         {
             double* temp = points->GetPoint(j);
             itk::Point<float, 3> vertex = GetItkPoint(temp);
             itk::Vector<double> v = GetItkVector(temp);
 
             itk::Vector<double, 3> dir(3);
             if (j<numPoints-1)
                 dir = GetItkVector(points->GetPoint(j+1))-v;
             else
                 dir = v-GetItkVector(points->GetPoint(j-1));
 
             itk::Index<3> idx;
             itk::ContinuousIndex<float, 3> contIndex;
             m_TissueMask->TransformPhysicalPointToIndex(vertex, idx);
             m_TissueMask->TransformPhysicalPointToContinuousIndex(vertex, contIndex);
 
             if (!m_UseInterpolation)    // use nearest neighbour interpolation
             {
                 if (!m_TissueMask->GetLargestPossibleRegion().IsInside(idx) || m_TissueMask->GetPixel(idx)<=0)
                     continue;
 
                 // generate signal for each fiber compartment
                 for (int k=0; k<m_FiberModels.size(); k++)
                 {
                     DoubleDwiType::Pointer doubleDwi = compartments.at(k);
                     m_FiberModels[k]->SetFiberDirection(dir);
                     DoubleDwiType::PixelType pix = doubleDwi->GetPixel(idx);
                     pix += segmentVolume*m_FiberModels[k]->SimulateMeasurement();
                     doubleDwi->SetPixel(idx, pix );
                     if (pix[baselineIndex]>maxVolume)
                         maxVolume = pix[baselineIndex];
                 }
 
                 continue;
             }
 
             double frac_x = contIndex[0] - idx[0];
             double frac_y = contIndex[1] - idx[1];
             double frac_z = contIndex[2] - idx[2];
             if (frac_x<0)
             {
                 idx[0] -= 1;
                 frac_x += 1;
             }
             if (frac_y<0)
             {
                 idx[1] -= 1;
                 frac_y += 1;
             }
             if (frac_z<0)
             {
                 idx[2] -= 1;
                 frac_z += 1;
             }
 
             frac_x = atan((0.5-frac_x)*m_InterpolationShrink)/interpFact + 0.5;
             frac_y = atan((0.5-frac_y)*m_InterpolationShrink)/interpFact + 0.5;
             frac_z = atan((0.5-frac_z)*m_InterpolationShrink)/interpFact + 0.5;
 
             // use trilinear interpolation
             itk::Index<3> newIdx;
             for (int x=0; x<2; x++)
             {
                 frac_x = 1-frac_x;
                 for (int y=0; y<2; y++)
                 {
                     frac_y = 1-frac_y;
                     for (int z=0; z<2; z++)
                     {
                         frac_z = 1-frac_z;
 
                         newIdx[0] = idx[0]+x;
                         newIdx[1] = idx[1]+y;
                         newIdx[2] = idx[2]+z;
 
                         double frac = frac_x*frac_y*frac_z;
 
                         // is position valid?
                         if (!m_TissueMask->GetLargestPossibleRegion().IsInside(newIdx) || m_TissueMask->GetPixel(newIdx)<=0)
                             continue;
 
                         // generate signal for each fiber compartment
                         for (int k=0; k<m_FiberModels.size(); k++)
                         {
                             DoubleDwiType::Pointer doubleDwi = compartments.at(k);
                             m_FiberModels[k]->SetFiberDirection(dir);
                             DoubleDwiType::PixelType pix = doubleDwi->GetPixel(newIdx);
                             pix += segmentVolume*frac*m_FiberModels[k]->SimulateMeasurement();
                             doubleDwi->SetPixel(newIdx, pix );
                             if (pix[baselineIndex]>maxVolume)
                                 maxVolume = pix[baselineIndex];
                         }
                     }
                 }
             }
         }
         ++disp;
     }
 
     MITK_INFO << "Generating signal of " << m_NonFiberModels.size() << " non-fiber compartments";
     ImageRegionIterator<ItkUcharImgType> it3(m_TissueMask, m_TissueMask->GetLargestPossibleRegion());
     boost::progress_display disp3(m_TissueMask->GetLargestPossibleRegion().GetNumberOfPixels());
     double voxelVolume = m_UpsampledSpacing[0]*m_UpsampledSpacing[1]*m_UpsampledSpacing[2];
 
     double fact = 1;
     if (m_FiberRadius<0.0001)
         fact = voxelVolume/maxVolume;
 
     while(!it3.IsAtEnd())
     {
         DoubleDwiType::IndexType index = it3.GetIndex();
 
         if (it3.Get()>0)
         {
             // get fiber volume fraction
             DoubleDwiType::Pointer fiberDwi = compartments.at(0);
             DoubleDwiType::PixelType fiberPix = fiberDwi->GetPixel(index); // intra axonal compartment
             if (fact>1) // auto scale intra-axonal if no fiber radius is specified
             {
                 fiberPix *= fact;
                 fiberDwi->SetPixel(index, fiberPix);
             }
             double f = fiberPix[baselineIndex];
 
             if (f>voxelVolume || f>0 && m_EnforcePureFiberVoxels)  // more fiber than space in voxel?
             {
                 fiberDwi->SetPixel(index, fiberPix*voxelVolume/f);
 
                 for (int i=1; i<m_FiberModels.size(); i++)
                 {
                     DoubleDwiType::PixelType pix; pix.Fill(0.0);
                     compartments.at(i)->SetPixel(index, pix);
                     m_VolumeFractions.at(i)->SetPixel(index, 1);
                 }
             }
             else
             {
                 m_VolumeFractions.at(0)->SetPixel(index, f);
 
                 double nonf = voxelVolume-f;    // non-fiber volume
                 double inter = 0;
                 if (m_FiberModels.size()>1)
                     inter = nonf * f/voxelVolume;   // intra-axonal fraction of non fiber compartment scales linearly with f
                 double other = nonf - inter;        // rest of compartment
                 double singleinter = inter/(m_FiberModels.size()-1);
 
                 // adjust non-fiber and intra-axonal signal
                 for (int i=1; i<m_FiberModels.size(); i++)
                 {
                     DoubleDwiType::Pointer doubleDwi = compartments.at(i);
                     DoubleDwiType::PixelType pix = doubleDwi->GetPixel(index);
                     if (pix[baselineIndex]>0)
                         pix /= pix[baselineIndex];
                     pix *= singleinter;
                     doubleDwi->SetPixel(index, pix);
                     m_VolumeFractions.at(i)->SetPixel(index, singleinter/voxelVolume);
                 }
                 for (int i=0; i<m_NonFiberModels.size(); i++)
                 {
                     DoubleDwiType::Pointer doubleDwi = compartments.at(i+m_FiberModels.size());
                     DoubleDwiType::PixelType pix = doubleDwi->GetPixel(index) + m_NonFiberModels[i]->SimulateMeasurement()*other*m_NonFiberModels[i]->GetWeight();
                     doubleDwi->SetPixel(index, pix);
                     m_VolumeFractions.at(i+m_FiberModels.size())->SetPixel(index, other/voxelVolume*m_NonFiberModels[i]->GetWeight());
                 }
             }
         }
         ++it3;
         ++disp3;
     }
 
     // do k-space stuff
     DoubleDwiType::Pointer doubleOutImage;
     if (m_FrequencyMap.IsNotNull() || !m_KspaceArtifacts.empty() || m_kOffset>0 || m_SimulateRelaxation || m_SimulateEddyCurrents || m_Upsampling>1.00001)
     {
         MITK_INFO << "Adjusting complex signal";
         doubleOutImage = DoKspaceStuff(compartments);
         m_SignalScale = 1;
     }
     else
     {
         MITK_INFO << "Summing compartments";
         doubleOutImage = compartments.at(0);
 
         for (int i=1; i<compartments.size(); i++)
         {
             itk::AddImageFilter< DoubleDwiType, DoubleDwiType, DoubleDwiType>::Pointer adder = itk::AddImageFilter< DoubleDwiType, DoubleDwiType, DoubleDwiType>::New();
             adder->SetInput1(doubleOutImage);
             adder->SetInput2(compartments.at(i));
             adder->Update();
             doubleOutImage = adder->GetOutput();
         }
     }
 
     MITK_INFO << "Finalizing image";
     unsigned int window = 0;
     unsigned int min = itk::NumericTraits<unsigned int>::max();
     ImageRegionIterator<OutputImageType> it4 (outImage, outImage->GetLargestPossibleRegion());
     DoubleDwiType::PixelType signal; signal.SetSize(m_FiberModels[0]->GetNumGradients());
     boost::progress_display disp4(outImage->GetLargestPossibleRegion().GetNumberOfPixels());
     while(!it4.IsAtEnd())
     {
         ++disp4;
         typename OutputImageType::IndexType index = it4.GetIndex();
         signal = doubleOutImage->GetPixel(index)*m_SignalScale;
 
         if (m_NoiseModel->GetNoiseVariance() > 0)
         {
             DoubleDwiType::PixelType accu = signal; accu.Fill(0.0);
             for (int i=0; i<m_NumberOfRepetitions; i++)
             {
                 DoubleDwiType::PixelType temp = signal;
                 m_NoiseModel->AddNoise(temp);
                 accu += temp;
             }
             signal = accu/m_NumberOfRepetitions;
         }
 
         for (int i=0; i<signal.Size(); i++)
         {
             if (signal[i]>0)
                 signal[i] = floor(signal[i]+0.5);
             else
                 signal[i] = ceil(signal[i]-0.5);
 
             if (!m_FiberModels.at(0)->IsBaselineIndex(i) && signal[i]>window)
                 window = signal[i];
             if (!m_FiberModels.at(0)->IsBaselineIndex(i) && signal[i]<min)
                 min = signal[i];
         }
         it4.Set(signal);
         ++it4;
     }
     window -= min;
     unsigned int level = window/2 + min;
     m_LevelWindow.SetLevelWindow(level, window);
     this->SetNthOutput(0, outImage);
 }
 
 template< class PixelType >
 itk::Point<float, 3> TractsToDWIImageFilter< PixelType >::GetItkPoint(double point[3])
 {
     itk::Point<float, 3> itkPoint;
     itkPoint[0] = point[0];
     itkPoint[1] = point[1];
     itkPoint[2] = point[2];
     return itkPoint;
 }
 
 template< class PixelType >
 itk::Vector<double, 3> TractsToDWIImageFilter< PixelType >::GetItkVector(double point[3])
 {
     itk::Vector<double, 3> itkVector;
     itkVector[0] = point[0];
     itkVector[1] = point[1];
     itkVector[2] = point[2];
     return itkVector;
 }
 
 template< class PixelType >
 vnl_vector_fixed<double, 3> TractsToDWIImageFilter< PixelType >::GetVnlVector(double point[3])
 {
     vnl_vector_fixed<double, 3> vnlVector;
     vnlVector[0] = point[0];
     vnlVector[1] = point[1];
     vnlVector[2] = point[2];
     return vnlVector;
 }
 
 template< class PixelType >
 vnl_vector_fixed<double, 3> TractsToDWIImageFilter< PixelType >::GetVnlVector(Vector<float,3>& vector)
 {
     vnl_vector_fixed<double, 3> vnlVector;
     vnlVector[0] = vector[0];
     vnlVector[1] = vector[1];
     vnlVector[2] = vector[2];
     return vnlVector;
 }
 
 }
diff --git a/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.h b/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.h
index cf847f9b48..4700a41dcd 100755
--- a/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.h
+++ b/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.h
@@ -1,153 +1,153 @@
 /*===================================================================
 
 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 __itkTractsToDWIImageFilter_h__
 #define __itkTractsToDWIImageFilter_h__
 
 // MITK
 #include <mitkFiberBundleX.h>
 #include <mitkDiffusionSignalModel.h>
 #include <mitkDiffusionNoiseModel.h>
 #include <mitkKspaceArtifact.h>
 
 // ITK
 #include <itkImage.h>
 #include <itkVectorImage.h>
 #include <itkImageSource.h>
 #include <itkVnlForwardFFTImageFilter.h>
 #include <itkVnlInverseFFTImageFilter.h>
 
 #include <cmath>
 
 
 namespace itk
 {
 
 /**
 * \brief Generates artificial diffusion weighted image volume from the input fiberbundle using a generic multicompartment model.   */
 
 template< class PixelType >
 class TractsToDWIImageFilter : public ImageSource< itk::VectorImage< PixelType, 3 > >
 {
 
 public:
 
     typedef TractsToDWIImageFilter      Self;
     typedef ImageSource< itk::VectorImage< PixelType, 3 > > Superclass;
     typedef SmartPointer< Self >        Pointer;
     typedef SmartPointer< const Self >  ConstPointer;
 
     typedef typename Superclass::OutputImageType                     OutputImageType;
     typedef itk::Image<double, 3>                           ItkDoubleImgType;
     typedef itk::Image<float, 3>                            ItkFloatImgType;
     typedef itk::Image<unsigned char, 3>                    ItkUcharImgType;
     typedef mitk::FiberBundleX::Pointer                     FiberBundleType;
     typedef itk::VectorImage< double, 3 >                   DoubleDwiType;
     typedef std::vector< mitk::KspaceArtifact<double>* >    KspaceArtifactList;
     typedef std::vector< mitk::DiffusionSignalModel<double>* >    DiffusionModelList;
     typedef itk::Matrix<double, 3, 3>                       MatrixType;
     typedef mitk::DiffusionNoiseModel<double>               NoiseModelType;
     typedef itk::Image< double, 2 >                         SliceType;
     typedef itk::VnlForwardFFTImageFilter<SliceType>::OutputImageType ComplexSliceType;
 
     itkNewMacro(Self)
     itkTypeMacro( TractsToDWIImageFilter, ImageToImageFilter )
 
     // input
     itkSetMacro( SignalScale, double )
     itkSetMacro( FiberRadius, double )
     itkSetMacro( InterpolationShrink, double )          ///< large values shrink (towards nearest neighbour interpolation), small values strech interpolation function (towards linear interpolation)
     itkSetMacro( VolumeAccuracy, unsigned int )         ///< determines fiber sampling density and thereby the accuracy of the fiber volume fraction
     itkSetMacro( FiberBundle, FiberBundleType )         ///< input fiber bundle
     itkSetMacro( Spacing, mitk::Vector3D )              ///< output image spacing
     itkSetMacro( Origin, mitk::Point3D )                ///< output image origin
     itkSetMacro( DirectionMatrix, MatrixType )          ///< output image rotation
     itkSetMacro( EnforcePureFiberVoxels, bool )         ///< treat all voxels containing at least one fiber as fiber-only (actually disable non-fiber compartments for this voxel).
     itkSetMacro( ImageRegion, ImageRegion<3> )          ///< output image size
     itkSetMacro( NumberOfRepetitions, unsigned int )    ///< number of acquisition repetitions to reduce noise (default is no additional repetition)
     itkSetMacro( TissueMask, ItkUcharImgType::Pointer ) ///< voxels outside of this binary mask contain only noise (are treated as air)
     void SetNoiseModel(NoiseModelType* noiseModel){ m_NoiseModel = noiseModel; }            ///< generates the noise added to the image values
     void SetFiberModels(DiffusionModelList modelList){ m_FiberModels = modelList; }         ///< generate signal of fiber compartments
     void SetNonFiberModels(DiffusionModelList modelList){ m_NonFiberModels = modelList; }   ///< generate signal of non-fiber compartments
     void SetKspaceArtifacts(KspaceArtifactList artifactList){ m_KspaceArtifacts = artifactList; }
     mitk::LevelWindow GetLevelWindow(){ return m_LevelWindow; }
     itkSetMacro( FrequencyMap, ItkDoubleImgType::Pointer )
     itkSetMacro( kOffset, double )
     itkSetMacro( tLine, double )
     itkSetMacro( tInhom, double )
     itkSetMacro( TE, double )
     itkSetMacro( UseInterpolation, bool )
     itkSetMacro( SimulateEddyCurrents, bool )
     itkSetMacro( SimulateRelaxation, bool )
     itkSetMacro( EddyGradientStrength, double )
     itkSetMacro( Upsampling, double )
 
     // output
     std::vector< ItkDoubleImgType::Pointer > GetVolumeFractions(){ return m_VolumeFractions; }
 
     void GenerateData();
 
 protected:
 
     TractsToDWIImageFilter();
     virtual ~TractsToDWIImageFilter();
     itk::Point<float, 3> GetItkPoint(double point[3]);
     itk::Vector<double, 3> GetItkVector(double point[3]);
     vnl_vector_fixed<double, 3> GetVnlVector(double point[3]);
     vnl_vector_fixed<double, 3> GetVnlVector(Vector< float, 3 >& vector);
 
     /** Transform generated image compartment by compartment, channel by channel and slice by slice using FFT and add k-space artifacts. */
     DoubleDwiType::Pointer DoKspaceStuff(std::vector< DoubleDwiType::Pointer >& images);
 
-    /** Rearrange FFT output to shift low frequencies to the iamge center (correct itk). */
-    TractsToDWIImageFilter::ComplexSliceType::Pointer RearrangeSlice(ComplexSliceType::Pointer slice);
+//    /** Rearrange FFT output to shift low frequencies to the iamge center (correct itk). */
+//    TractsToDWIImageFilter::ComplexSliceType::Pointer RearrangeSlice(ComplexSliceType::Pointer slice);
 
     itk::Vector<double>                 m_Spacing;              ///< output image spacing
     itk::Vector<double>                 m_UpsampledSpacing;
     mitk::Point3D                       m_Origin;               ///< output image origin
     MatrixType                          m_DirectionMatrix;      ///< output image rotation
     ImageRegion<3>                      m_ImageRegion;          ///< output image size
     ImageRegion<3>                      m_UpsampledImageRegion;
     ItkUcharImgType::Pointer            m_TissueMask;           ///< voxels outside of this binary mask contain only noise (are treated as air)
     ItkDoubleImgType::Pointer           m_FrequencyMap;         ///< map of the B0 inhomogeneities
     double                              m_kOffset;
     double                              m_tLine;
     double                              m_TE;
     double                              m_tInhom;
     FiberBundleType                     m_FiberBundle;          ///< input fiber bundle
     DiffusionModelList                  m_FiberModels;          ///< generate signal of fiber compartments
     DiffusionModelList                  m_NonFiberModels;       ///< generate signal of non-fiber compartments
     KspaceArtifactList                  m_KspaceArtifacts;
     NoiseModelType*                     m_NoiseModel;           ///< generates the noise added to the image values
     bool                                m_CircleDummy;
     unsigned int                        m_VolumeAccuracy;
     double                              m_Upsampling;           ///< causes ringing artifacts
     unsigned int                        m_NumberOfRepetitions;
     bool                                m_EnforcePureFiberVoxels;
     double                              m_InterpolationShrink;
     double                              m_FiberRadius;
     double                              m_SignalScale;
     mitk::LevelWindow                   m_LevelWindow;
     bool                                m_UseInterpolation;
     std::vector< ItkDoubleImgType::Pointer >    m_VolumeFractions;  ///< one double image for each compartment containing the corresponding volume fraction per voxel
     bool                                m_SimulateRelaxation;
     bool                                m_SimulateEddyCurrents;
     double                              m_EddyGradientStrength;
 };
 }
 
 #include "itkTractsToDWIImageFilter.cpp"
 
 #endif