diff --git a/Modules/DiffusionImaging/Algorithms/itkResidualImageFilter.txx b/Modules/DiffusionImaging/Algorithms/itkResidualImageFilter.txx
index b6dda78610..591f8f5d30 100644
--- a/Modules/DiffusionImaging/Algorithms/itkResidualImageFilter.txx
+++ b/Modules/DiffusionImaging/Algorithms/itkResidualImageFilter.txx
@@ -1,112 +1,107 @@
 /*=========================================================================
 
 Program:   Tensor ToolKit - TTK
 Module:    $URL: svn://scm.gforge.inria.fr/svn/ttk/trunk/Algorithms/itkTensorImageToDiffusionImageFilter.txx $
 Language:  C++
 Date:      $Date: 2010-06-07 13:39:13 +0200 (Mo, 07 Jun 2010) $
 Version:   $Revision: 68 $
 
 Copyright (c) INRIA 2010. All rights reserved.
 See LICENSE.txt for details.
 
 This software is distributed WITHOUT ANY WARRANTY; without even
 the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
 PURPOSE.  See the above copyright notices for more information.
 
 =========================================================================*/
 #ifndef _itk_ResidualImageFilter_txx_
 #define _itk_ResidualImageFilter_txx_
 #endif
 
 #include "itkResidualImageFilter.h"
 #include <mitkCommon.h>
 
 namespace itk
 {
 
 
 
 
   template <class TInputScalarType, class TOutputScalarType>
   void
   ResidualImageFilter<TInputScalarType, TOutputScalarType>
   ::GenerateData()
   {
     typename InputImageType::SizeType size = this->GetInput()->GetLargestPossibleRegion().GetSize();
     typename InputImageType::SizeType size2 = m_SecondDiffusionImage->GetLargestPossibleRegion().GetSize();
 
     if(size != size2)
     {
       MITK_ERROR << "Sizes do not match";
       return;
     }
 
     // Initialize output image
     typename OutputImageType::Pointer outputImage =
         static_cast< OutputImageType * >(this->ProcessObject::GetOutput(0));
 
     outputImage->SetSpacing( this->GetInput()->GetSpacing() );   // Set the image spacing
     outputImage->SetOrigin( this->GetInput()->GetOrigin() );     // Set the image origin
     outputImage->SetDirection( this->GetInput()->GetDirection() );  // Set the image direction
     outputImage->SetRegions( this->GetInput()->GetLargestPossibleRegion() );
     outputImage->Allocate();
     outputImage->FillBuffer(0.0);
 
     for(int x=0; x<size[0]; x++)
     {
       for(int y=0; y<size[1]; y++)
       {
         for(int z=0; z<size[2]; z++)
         {
           itk::Index<3> ix;
           ix[0] = x;
           ix[1] = y;
           ix[2] = z;
 
           typename InputImageType::PixelType p1 = this->GetInput()->GetPixel(ix);
           typename InputImageType::PixelType p2 = m_SecondDiffusionImage->GetPixel(ix);
 
 
 
           if(p1.GetSize() != p2.GetSize())
           {
             MITK_ERROR << "Vector sizes do not match";
             return;
           }
 
           float res = 0;
 
           for(int i = 0; i<p1.GetSize(); i++)
           {
             float val1 = (float)p1.GetElement(i);
             float val2 = (float)p2.GetElement(i);
 
             res += abs(val1-val2);
           }
 
 
           res = res/p1.GetSize();
-          if(res!=0.0)
-          {
-            std::cout << "not 0";
-          }
-
 
           outputImage->SetPixel(ix, res);
 
         }
       }
     }
 
    // Superclass::SetNthInput(0, outputImage);
 
 
 
   }
 
 
 
 
 
 
 } // end of namespace
diff --git a/Modules/DiffusionImaging/Algorithms/itkTensorImageToDiffusionImageFilter.h b/Modules/DiffusionImaging/Algorithms/itkTensorImageToDiffusionImageFilter.h
index e8890d6b2b..8f1aaabe36 100644
--- a/Modules/DiffusionImaging/Algorithms/itkTensorImageToDiffusionImageFilter.h
+++ b/Modules/DiffusionImaging/Algorithms/itkTensorImageToDiffusionImageFilter.h
@@ -1,117 +1,128 @@
 /*=========================================================================
 
 Program:   Tensor ToolKit - TTK
 Module:    $URL: svn://scm.gforge.inria.fr/svn/ttk/trunk/Algorithms/itkTensorImageToDiffusionImageFilter.h $
 Language:  C++
 Date:      $Date: 2010-06-07 13:39:13 +0200 (Mo, 07 Jun 2010) $
 Version:   $Revision: 68 $
 
 Copyright (c) INRIA 2010. All rights reserved.
 See LICENSE.txt for details.
 
 This software is distributed WITHOUT ANY WARRANTY; without even
 the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
 PURPOSE.  See the above copyright notices for more information.
 
 =========================================================================*/
 #ifndef _itk_TensorImageToDiffusionImageFilter_h_
 #define _itk_TensorImageToDiffusionImageFilter_h_
 
 #include "itkImageToImageFilter.h"
 #include <itkDiffusionTensor3D.h>
 
 namespace itk
 {
 
   template <class TInputScalarType, class TOutputScalarType>
   class TensorImageToDiffusionImageFilter
     : public ImageToImageFilter<itk::Image<itk::DiffusionTensor3D<TInputScalarType>,3>, itk::VectorImage<TOutputScalarType,3> >
   {
 
   public:
 
     typedef TInputScalarType                          InputScalarType;
     typedef itk::DiffusionTensor3D<InputScalarType>   InputPixelType;
     typedef itk::Image<InputPixelType,3>              InputImageType;
     typedef typename InputImageType::RegionType       InputImageRegionType;
 
     typedef TOutputScalarType                         OutputScalarType;
     typedef itk::VectorImage<OutputScalarType,3>      OutputImageType;
     typedef typename OutputImageType::PixelType       OutputPixelType;
     typedef typename OutputImageType::RegionType      OutputImageRegionType;
 
     typedef OutputScalarType                          BaselineScalarType;
     typedef BaselineScalarType                        BaselinePixelType;
     typedef typename itk::Image<BaselinePixelType,3>  BaselineImageType;
     typedef typename BaselineImageType::RegionType    BaselineImageRegionType;
 
     typedef TensorImageToDiffusionImageFilter Self;
     typedef ImageToImageFilter<InputImageType, OutputImageType> Superclass;
 
     typedef SmartPointer<Self> Pointer;
     typedef SmartPointer<const Self> ConstPointer;
 
     itkTypeMacro (TensorImageToDiffusionImageFilter, ImageToImageFilter);
 
     itkStaticConstMacro (ImageDimension, unsigned int,
       OutputImageType::ImageDimension);
 
     itkNewMacro (Self);
 
     typedef Vector<double,3>          GradientType;
     typedef std::vector<GradientType> GradientListType;
 
     /** Manually Set/Get a list of gradients */
     void SetGradientList(const GradientListType list)
     {
       m_GradientList = list;
       this->Modified();
     }
     GradientListType GetGradientList(void) const
     {return m_GradientList;}
 
 
     void SetBValue( const double& bval)
     { m_BValue = bval; }
 
+    itkSetMacro(Min, OutputScalarType);
+    itkSetMacro(Max, OutputScalarType);
+
+
   protected:
     TensorImageToDiffusionImageFilter()
     {
       m_BValue = 1.0;
       m_BaselineImage = 0;
+      m_Min = 0.0;
+      m_Max = 10000.0;
     };
     ~TensorImageToDiffusionImageFilter(){};
 
     void PrintSelf (std::ostream& os, Indent indent) const
     {
       Superclass::PrintSelf (os, indent);      
     }
 
     void BeforeThreadedGenerateData( void );
 
     void ThreadedGenerateData( const 
       OutputImageRegionType &outputRegionForThread, int);
   
     //void GenerateData();
 
+
+
   private:
 
     TensorImageToDiffusionImageFilter (const Self&);
     void operator=(const Self&);
 
     GradientListType                     m_GradientList;
     double                               m_BValue;
     typename BaselineImageType::Pointer  m_BaselineImage;
 
+    OutputScalarType                     m_Min;
+    OutputScalarType                     m_Max;
+
   };    
 
 
 } // end of namespace
 
 
 #ifndef ITK_MANUAL_INSTANTIATION
 #include "itkTensorImageToDiffusionImageFilter.txx"
 #endif
 
 
 #endif
diff --git a/Plugins/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.cpp b/Plugins/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.cpp
index b6cfc94d16..538d2636a3 100644
--- a/Plugins/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.cpp
+++ b/Plugins/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.cpp
@@ -1,979 +1,1031 @@
 /*=========================================================================
 
 Program:   Medical Imaging & Interaction Toolkit
 Module:    $RCSfile$
 Language:  C++
 Date:      $Date: 2009-05-28 17:19:30 +0200 (Do, 28 Mai 2009) $
 Version:   $Revision: 17495 $
 
 Copyright (c) German Cancer Research Center, Division of Medical and
 Biological Informatics. All rights reserved.
 See MITKCopyright.txt or http://www.mitk.org/copyright.html for details.
 
 This software is distributed WITHOUT ANY WARRANTY; without even
 the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
 PURPOSE.  See the above copyright notices for more information.
 
 =========================================================================*/
 
 #include "QmitkTensorReconstructionView.h"
 #include "mitkDiffusionImagingConfigure.h"
 
 // qt includes
 #include <QMessageBox>
 
 // itk includes
 #include "itkTimeProbe.h"
 //#include "itkTensor.h"
 
 // mitk includes
 #include "mitkProgressBar.h"
 #include "mitkStatusBar.h"
 
 #include "mitkNodePredicateDataType.h"
 #include "QmitkDataStorageComboBox.h"
 #include "QmitkStdMultiWidget.h"
 
 #include "mitkTeemDiffusionTensor3DReconstructionImageFilter.h"
 #include "itkDiffusionTensor3DReconstructionImageFilter.h"
 #include "itkTensorImageToDiffusionImageFilter.h"
 #include "itkPointShell.h"
 #include "itkVector.h"
 
 #include "mitkProperties.h"
 #include "mitkDataNodeObject.h"
 #include "mitkOdfNormalizationMethodProperty.h"
 #include "mitkOdfScaleByProperty.h"
 #include "mitkDiffusionImageMapper.h"
+#include "mitkLookupTableProperty.h"
+#include "mitkLookupTable.h"
+#include "mitkImageStatisticsHolder.h"
 
 #include "berryIStructuredSelection.h"
 #include "berryIWorkbenchWindow.h"
 #include "berryISelectionService.h"
 
 #include <itkTensorImageToQBallImageFilter.h>
 #include <itkResidualImageFilter.h>
 
 const std::string QmitkTensorReconstructionView::VIEW_ID =
 "org.mitk.views.tensorreconstruction";
 
 #define DI_INFO MITK_INFO("DiffusionImaging")
 
 typedef float TTensorPixelType;
 
 using namespace berry;
 
 struct TrSelListener : ISelectionListener
 {
 
   berryObjectMacro(TrSelListener);
 
   TrSelListener(QmitkTensorReconstructionView* view)
   {
     m_View = view;
   }
 
   void DoSelectionChanged(ISelection::ConstPointer selection)
   {
     //    if(!m_View->IsVisible())
     //      return;
     // save current selection in member variable
     m_View->m_CurrentSelection = selection.Cast<const IStructuredSelection>();
 
     // do something with the selected items
     if(m_View->m_CurrentSelection)
     {
       bool foundDwiVolume = false;
       bool foundTensorVolume = false;
 
       // iterate selection
       for (IStructuredSelection::iterator i = m_View->m_CurrentSelection->Begin();
         i != m_View->m_CurrentSelection->End(); ++i)
       {
 
         // extract datatree node
         if (mitk::DataNodeObject::Pointer nodeObj = i->Cast<mitk::DataNodeObject>())
         {
           mitk::DataNode::Pointer node = nodeObj->GetDataNode();
 
           // only look at interesting types
           if(QString("DiffusionImage").compare(node->GetData()->GetNameOfClass())==0)
           {
             foundDwiVolume = true;
           }
 
           // only look at interesting types
           if(QString("TensorImage").compare(node->GetData()->GetNameOfClass())==0)
           {
             foundTensorVolume = true;
           }
         }
       }
 
       m_View->m_Controls->m_ItkReconstruction->setEnabled(foundDwiVolume);
       m_View->m_Controls->m_TeemReconstruction->setEnabled(foundDwiVolume);
 
       m_View->m_Controls->m_TensorsToDWIButton->setEnabled(foundTensorVolume);
       m_View->m_Controls->m_TensorsToQbiButton->setEnabled(foundTensorVolume);
 
       m_View->m_Controls->m_ResidualButton->setEnabled(foundDwiVolume && foundTensorVolume);
 
 
     }
   }
 
   void SelectionChanged(IWorkbenchPart::Pointer part, ISelection::ConstPointer selection)
   {
     // check, if selection comes from datamanager
     if (part)
     {
       QString partname(part->GetPartName().c_str());
       if(partname.compare("Datamanager")==0)
       {
 
         // apply selection
         DoSelectionChanged(selection);
 
       }
     }
   }
 
   QmitkTensorReconstructionView* m_View;
 };
 
 QmitkTensorReconstructionView::QmitkTensorReconstructionView()
 : QmitkFunctionality(),
 m_Controls(NULL),
 m_MultiWidget(NULL)
 {
 }
 
 QmitkTensorReconstructionView::QmitkTensorReconstructionView(const QmitkTensorReconstructionView& other)
 {
   Q_UNUSED(other)
   throw std::runtime_error("Copy constructor not implemented");
 }
 
 QmitkTensorReconstructionView::~QmitkTensorReconstructionView()
 {
   this->GetSite()->GetWorkbenchWindow()->GetSelectionService()->RemovePostSelectionListener(/*"org.mitk.views.datamanager",*/ m_SelListener);
 }
 
 void QmitkTensorReconstructionView::CreateQtPartControl(QWidget *parent)
 {
   if (!m_Controls)
   {
     // create GUI widgets
     m_Controls = new Ui::QmitkTensorReconstructionViewControls;
     m_Controls->setupUi(parent);
     this->CreateConnections();
 
     QStringList items;
     items << "LLS (Linear Least Squares)"
       << "MLE (Maximum Likelihood)"
       << "NLS (Nonlinear Least Squares)"
       << "WLS (Weighted Least Squares)";
     m_Controls->m_TensorEstimationTeemEstimationMethodCombo->addItems(items);
     m_Controls->m_TensorEstimationTeemEstimationMethodCombo->setCurrentIndex(0);
 
     m_Controls->m_TensorEstimationManualThreashold->setChecked(false);
     m_Controls->m_TensorEstimationTeemSigmaEdit->setText("NaN");
     m_Controls->m_TensorEstimationTeemNumItsSpin->setValue(1);
     m_Controls->m_TensorEstimationTeemFuzzyEdit->setText("0.0");
     m_Controls->m_TensorEstimationTeemMinValEdit->setText("1.0");
 
     m_Controls->m_TensorEstimationTeemNumItsLabel_2->setEnabled(true);
     m_Controls->m_TensorEstimationTeemNumItsSpin->setEnabled(true);
 
     m_Controls->m_TensorsToDWIBValueEdit->setText("1000");
 
     Advanced1CheckboxClicked();
     Advanced2CheckboxClicked();
     TeemCheckboxClicked();
 
 #ifndef DIFFUSION_IMAGING_EXTENDED
     m_Controls->m_TeemToggle->setVisible(false);
 #endif
 
     // define data type for combobox
     //m_Controls->m_ImageSelector->SetDataStorage( this->GetDefaultDataStorage() );
     //m_Controls->m_ImageSelector->SetPredicate( mitk::NodePredicateDataType::New("DiffusionImage") );
   }
 
   m_SelListener = berry::ISelectionListener::Pointer(new TrSelListener(this));
   this->GetSite()->GetWorkbenchWindow()->GetSelectionService()->AddPostSelectionListener(/*"org.mitk.views.datamanager",*/ m_SelListener);
   berry::ISelection::ConstPointer sel(
     this->GetSite()->GetWorkbenchWindow()->GetSelectionService()->GetSelection("org.mitk.views.datamanager"));
   m_CurrentSelection = sel.Cast<const IStructuredSelection>();
   m_SelListener.Cast<TrSelListener>()->DoSelectionChanged(sel);
 }
 
 void QmitkTensorReconstructionView::StdMultiWidgetAvailable (QmitkStdMultiWidget &stdMultiWidget)
 {
   berry::ISelection::ConstPointer sel(
     this->GetSite()->GetWorkbenchWindow()->GetSelectionService()->GetSelection("org.mitk.views.datamanager"));
   m_CurrentSelection = sel.Cast<const IStructuredSelection>();
   m_SelListener.Cast<TrSelListener>()->DoSelectionChanged(sel);
   m_MultiWidget = &stdMultiWidget;
 }
 
 void QmitkTensorReconstructionView::StdMultiWidgetNotAvailable()
 {
   m_MultiWidget = NULL;
 }
 
 void QmitkTensorReconstructionView::CreateConnections()
 {
   if ( m_Controls )
   {
     connect( (QObject*)(m_Controls->m_TeemToggle), SIGNAL(clicked()), this, SLOT(TeemCheckboxClicked()) );
     connect( (QObject*)(m_Controls->m_ItkReconstruction), SIGNAL(clicked()), this, SLOT(ItkReconstruction()) );
     connect( (QObject*)(m_Controls->m_TeemReconstruction), SIGNAL(clicked()), this, SLOT(TeemReconstruction()) );
     connect( (QObject*)(m_Controls->m_TensorEstimationTeemEstimationMethodCombo), SIGNAL(currentIndexChanged(int)), this, SLOT(MethodChoosen(int)) );
     connect( (QObject*)(m_Controls->m_Advanced1), SIGNAL(clicked()), this, SLOT(Advanced1CheckboxClicked()) );
     connect( (QObject*)(m_Controls->m_Advanced2), SIGNAL(clicked()), this, SLOT(Advanced2CheckboxClicked()) );
     connect( (QObject*)(m_Controls->m_TensorEstimationManualThreashold), SIGNAL(clicked()), this, SLOT(ManualThresholdClicked()) );
     connect( (QObject*)(m_Controls->m_TensorsToDWIButton), SIGNAL(clicked()), this, SLOT(TensorsToDWI()) );
     connect( (QObject*)(m_Controls->m_TensorsToQbiButton), SIGNAL(clicked()), this, SLOT(TensorsToQbi()) );
     connect( (QObject*)(m_Controls->m_ResidualButton), SIGNAL(clicked()), this, SLOT(ResidualCalculation()) );
   }
 }
 
 void QmitkTensorReconstructionView::TeemCheckboxClicked()
 {
   m_Controls->groupBox_3->setVisible(m_Controls->
     m_TeemToggle->isChecked());
 }
 
 void QmitkTensorReconstructionView::Advanced1CheckboxClicked()
 {
   bool check = m_Controls->
     m_Advanced1->isChecked();
 
   m_Controls->frame->setVisible(check);
 }
 
 void QmitkTensorReconstructionView::Advanced2CheckboxClicked()
 {
   bool check = m_Controls->
     m_Advanced2->isChecked();
 
   m_Controls->frame_2->setVisible(check);
 }
 
 void QmitkTensorReconstructionView::ManualThresholdClicked()
 {
   m_Controls->m_TensorReconstructionThreasholdEdit_2->setEnabled(
     m_Controls->m_TensorEstimationManualThreashold->isChecked());
 }
 
 void QmitkTensorReconstructionView::Activated()
 {
   QmitkFunctionality::Activated();
 }
 
 void QmitkTensorReconstructionView::Deactivated()
 {
   QmitkFunctionality::Deactivated();
 }
 
 void QmitkTensorReconstructionView::MethodChoosen(int method)
 {
   m_Controls->m_TensorEstimationTeemNumItsLabel_2->setEnabled(method==3);
   m_Controls->m_TensorEstimationTeemNumItsSpin->setEnabled(method==3);
 }
 
 void QmitkTensorReconstructionView::ResidualCalculation()
 {
   // Extract dwi and dti from current selection
   // In case of multiple selections, take the first one, since taking all combinations is not meaningful
   if(m_CurrentSelection)
   {
     mitk::DataStorage::SetOfObjects::Pointer set =
       mitk::DataStorage::SetOfObjects::New();
 
     mitk::DiffusionImage<DiffusionPixelType>::Pointer diffImage
         = mitk::DiffusionImage<DiffusionPixelType>::New();
 
     typedef float                                       TTensorPixelType;
     typedef itk::DiffusionTensor3D< TTensorPixelType >  TensorPixelType;
     typedef itk::Image< TensorPixelType, 3 >            TensorImageType;
 
     TensorImageType::Pointer tensorImage;
 
     std::string nodename;
 
 
     for (IStructuredSelection::iterator i = m_CurrentSelection->Begin();
       i != m_CurrentSelection->End();
       ++i)
     {
 
       if (mitk::DataNodeObject::Pointer nodeObj = i->Cast<mitk::DataNodeObject>())
       {
         mitk::DataNode::Pointer node = nodeObj->GetDataNode();
         if(QString("DiffusionImage").compare(node->GetData()->GetNameOfClass())==0)
         {
           diffImage = static_cast<mitk::DiffusionImage<DiffusionPixelType>*>((node)->GetData());
         }
         else if((QString("TensorImage").compare(node->GetData()->GetNameOfClass())==0))
         {
           mitk::TensorImage* mitkVol;
           mitkVol = static_cast<mitk::TensorImage*>((node)->GetData());
           mitk::CastToItkImage<TensorImageType>(mitkVol, tensorImage);
           node->GetStringProperty("name", nodename);
         }
       }
     }
 
 
 
     typedef itk::TensorImageToDiffusionImageFilter<
       TTensorPixelType, DiffusionPixelType > FilterType;
 
     FilterType::GradientListType gradientList;
     mitk::DiffusionImage<DiffusionPixelType>::GradientDirectionContainerType* gradients
         = diffImage->GetDirections();
 
     // Copy gradients vectors from gradients to gradientList
     for(int i=0; i<gradients->Size(); i++)
     {
       mitk::DiffusionImage<DiffusionPixelType>::GradientDirectionType vec = gradients->at(i);
       itk::Vector<double,3> grad;
 
       grad[0] = vec[0];
       grad[1] = vec[1];
       grad[2] = vec[2];
 
       gradientList.push_back(grad);
     }
 
-
+    // Find the min and the max values from a baseline image
+    mitk::ImageStatisticsHolder *stats = diffImage->GetStatistics();
 
     //Initialize filter that calculates the modeled diffusion weighted signals
     FilterType::Pointer filter = FilterType::New();
     filter->SetInput( tensorImage );
     filter->SetBValue(diffImage->GetB_Value());
     filter->SetGradientList(gradientList);
+    filter->SetMin(stats->GetScalarValueMin());
+    filter->SetMax(stats->GetScalarValueMax());
     filter->Update();
 
 
     // TENSORS TO DATATREE
     mitk::DiffusionImage<DiffusionPixelType>::Pointer image = mitk::DiffusionImage<DiffusionPixelType>::New();
     image->SetVectorImage( filter->GetOutput() );
     image->SetB_Value(diffImage->GetB_Value());
     image->SetDirections(gradientList);
     image->SetOriginalDirections(gradientList);
     image->InitializeFromVectorImage();
     mitk::DataNode::Pointer node=mitk::DataNode::New();
     node->SetData( image );
 
 
     QString newname;
     newname = newname.append(nodename.c_str());
     newname = newname.append("_dwi");
     node->SetName(newname.toAscii());
 
 
     GetDefaultDataStorage()->Add(node);    
 
 
     typedef itk::ResidualImageFilter<DiffusionPixelType, float> ResidualImageFilterType;
 
     ResidualImageFilterType::Pointer residualFilter = ResidualImageFilterType::New();
     residualFilter->SetInput(diffImage->GetVectorImage());
     residualFilter->SetSecondDiffusionImage(image->GetVectorImage());
     residualFilter->Update();
 
     itk::Image<float, 3>::Pointer residualImage = itk::Image<float, 3>::New();
     residualImage = residualFilter->GetOutput();
 
     mitk::Image::Pointer mitkResImg = mitk::Image::New();
 
     mitk::CastToMitkImage(residualImage, mitkResImg);
-   // mitkResImg->InitializeByItk(residualImage.GetPointer());
-  //  image->SetVolume( residualImage->GetBufferPointer() );
 
-   // mitk::CastToMitkImage(residualImage, mitkResImg);
+    stats = mitkResImg->GetStatistics();
+    float min = stats->GetScalarValueMin();
+    float max = stats->GetScalarValueMax();
+
+    mitk::LookupTableProperty::Pointer lutProp = mitk::LookupTableProperty::New();
+    mitk::LookupTable::Pointer lut = mitk::LookupTable::New();
+
+
+    vtkSmartPointer<vtkLookupTable> lookupTable =
+        vtkSmartPointer<vtkLookupTable>::New();
+
+    lookupTable->SetTableRange(min, max);
+
+
+
+
+    // If you don't want to use the whole color range, you can use
+    // SetValueRange, SetHueRange, and SetSaturationRange
+    lookupTable->Build();
+
+    int size =lookupTable->GetTable()->GetSize();
+
+    vtkSmartPointer<vtkLookupTable> reversedlookupTable =
+        vtkSmartPointer<vtkLookupTable>::New();
+    reversedlookupTable->SetTableRange(min+1, max);
+    reversedlookupTable->Build();
+
+    for(int i=0; i<=256; i++)
+    {
+      double* rgba = reversedlookupTable->GetTableValue(255-i);
+
+      std::cout << rgba[0] << ' ' << rgba[1] << ' ' << rgba[2] << ' ' << rgba[3] << '\n';
+      lookupTable->SetTableValue(i, rgba[0], rgba[1], rgba[2], rgba[3]);
+    }
+    std::cout << std::endl;
+
+
+    lut->SetVtkLookupTable(lookupTable);
+    lutProp->SetLookupTable(lut);
+
+    // Create lookuptable
+
     mitk::DataNode::Pointer resNode=mitk::DataNode::New();
     resNode->SetData( mitkResImg );
     resNode->SetName("Residual Image");
+
+    resNode->SetProperty("LookupTable", lutProp);
+
+    bool b;
+    resNode->GetBoolProperty("use color", b);
+    resNode->SetBoolProperty("use color", false);
+
     GetDefaultDataStorage()->Add(resNode);
 
     m_MultiWidget->RequestUpdate();
 
 
   }
 }
 
 void QmitkTensorReconstructionView::ItkReconstruction()
 {
   Reconstruct(0);
 }
 
 void QmitkTensorReconstructionView::TeemReconstruction()
 {
   Reconstruct(1);
 }
 
 void QmitkTensorReconstructionView::Reconstruct(int method)
 {
   if (m_CurrentSelection)
   {
     mitk::DataStorage::SetOfObjects::Pointer set =
       mitk::DataStorage::SetOfObjects::New();
 
     int at = 0;
     for (IStructuredSelection::iterator i = m_CurrentSelection->Begin();
       i != m_CurrentSelection->End();
       ++i)
     {
 
       if (mitk::DataNodeObject::Pointer nodeObj = i->Cast<mitk::DataNodeObject>())
       {
         mitk::DataNode::Pointer node = nodeObj->GetDataNode();
         if(QString("DiffusionImage").compare(node->GetData()->GetNameOfClass())==0)
         {
           set->InsertElement(at++, node);
         }
       }
     }
 
     if(method == 0)
     {
       ItkTensorReconstruction(set);
     }
 
     if(method == 1)
     {
       TeemTensorReconstruction(set);
     }
 
   }
 }
 
 void QmitkTensorReconstructionView::ItkTensorReconstruction
 (mitk::DataStorage::SetOfObjects::Pointer inImages)
 {
   try
   {
     itk::TimeProbe clock;
 
     int nrFiles = inImages->size();
     if (!nrFiles) return;
 
     QString status;
     mitk::ProgressBar::GetInstance()->AddStepsToDo(nrFiles);
 
     mitk::DataStorage::SetOfObjects::const_iterator itemiter( inImages->begin() );
     mitk::DataStorage::SetOfObjects::const_iterator itemiterend( inImages->end() );
 
     std::vector<mitk::DataNode::Pointer> nodes;
     while ( itemiter != itemiterend ) // for all items
     {
 
       mitk::DiffusionImage<DiffusionPixelType>* vols =
         static_cast<mitk::DiffusionImage<DiffusionPixelType>*>(
         (*itemiter)->GetData());
 
       std::string nodename;
       (*itemiter)->GetStringProperty("name", nodename);
       ++itemiter;
 
       // TENSOR RECONSTRUCTION
       clock.Start();
       MBI_INFO << "Tensor reconstruction ";
       mitk::StatusBar::GetInstance()->DisplayText(status.sprintf(
         "Tensor reconstruction for %s", nodename.c_str()).toAscii());
       typedef itk::DiffusionTensor3DReconstructionImageFilter<
         DiffusionPixelType, DiffusionPixelType, TTensorPixelType > TensorReconstructionImageFilterType;
       TensorReconstructionImageFilterType::Pointer tensorReconstructionFilter =
         TensorReconstructionImageFilterType::New();
       tensorReconstructionFilter->SetGradientImage( vols->GetDirections(), vols->GetVectorImage() );
       tensorReconstructionFilter->SetBValue(vols->GetB_Value());
       tensorReconstructionFilter->SetThreshold( m_Controls->m_TensorReconstructionThreasholdEdit->text().toFloat() );
       tensorReconstructionFilter->Update();
       clock.Stop();
       MBI_DEBUG << "took " << clock.GetMeanTime() << "s.";
 
       // TENSORS TO DATATREE
       mitk::TensorImage::Pointer image = mitk::TensorImage::New();
 
 
       typedef itk::Image<itk::DiffusionTensor3D<TTensorPixelType>, 3> TensorImageType;
 
       TensorImageType::Pointer tensorImage;
       tensorImage = tensorReconstructionFilter->GetOutput();
 
 
 
 
       // Check the tensor for negative eigenvalues
       if(m_Controls->m_CheckNegativeEigenvalues->isChecked())
       {
         typedef itk::ImageRegionIterator<TensorImageType> TensorImageIteratorType;
         TensorImageIteratorType tensorIt(tensorImage, tensorImage->GetRequestedRegion());
         tensorIt.GoToBegin();
 
         while(!tensorIt.IsAtEnd())
         {
 
           typedef itk::DiffusionTensor3D<TTensorPixelType> TensorType;
           //typedef itk::Tensor<TTensorPixelType, 3> TensorType2;
 
           TensorType tensor = tensorIt.Get();
          // TensorType2 tensor2;
 
           /*
           for(int i=0; i<tensor.GetNumberOfComponents(); i++)
           {
             tensor2.SetNthComponent(i, tensor.GetNthComponent(i));
           }
 
           typedef vnl_symmetric_eigensystem< TTensorPixelType >  SymEigenSystemType;
           SymEigenSystemType eig (tensor2.GetVnlMatrix());
           for(unsigned int i=0; i<eig.D.size(); i++)
           {
             if (eig.D[i] < 0.0 )
             {
               tensor.Fill(0.0);
               tensorIt.Set(tensor);
             }
           }*/
 
 
           TensorType::EigenValuesArrayType ev;
           tensor.ComputeEigenValues(ev);
           for(unsigned int i=0; i<ev.Size(); i++)
           {
             if(ev[i] < 0.0)
             {
               tensor.Fill(0.0);
               tensorIt.Set(tensor);
               break;
             }
           }
 
 
           ++tensorIt;
         }
       }
 
 
       image->InitializeByItk( tensorImage.GetPointer() );
       image->SetVolume( tensorReconstructionFilter->GetOutput()->GetBufferPointer() );
       mitk::DataNode::Pointer node=mitk::DataNode::New();
       node->SetData( image );
 
       QString newname;
       newname = newname.append(nodename.c_str());
       newname = newname.append("_dti");
 
       SetDefaultNodeProperties(node, newname.toStdString());
       nodes.push_back(node);
 
       mitk::ProgressBar::GetInstance()->Progress();
 
     }
 
     std::vector<mitk::DataNode::Pointer>::iterator nodeIt;
     for(nodeIt = nodes.begin(); nodeIt != nodes.end(); ++nodeIt)
       GetDefaultDataStorage()->Add(*nodeIt);
 
     mitk::StatusBar::GetInstance()->DisplayText(status.sprintf("Finished Processing %d Files", nrFiles).toAscii());
     m_MultiWidget->RequestUpdate();
 
   }
   catch (itk::ExceptionObject &ex)
   {
     MBI_INFO << ex ;
     return ;
   }
 }
 
 
 
 void QmitkTensorReconstructionView::TeemTensorReconstruction
 (mitk::DataStorage::SetOfObjects::Pointer inImages)
 {
   try
   {
     itk::TimeProbe clock;
 
     int nrFiles = inImages->size();
     if (!nrFiles) return;
 
     QString status;
     mitk::ProgressBar::GetInstance()->AddStepsToDo(nrFiles);
 
     mitk::DataStorage::SetOfObjects::const_iterator itemiter( inImages->begin() );
     mitk::DataStorage::SetOfObjects::const_iterator itemiterend( inImages->end() );
 
     std::vector<mitk::DataNode::Pointer> nodes;
     while ( itemiter != itemiterend ) // for all items
     {
 
       mitk::DiffusionImage<DiffusionPixelType>* vols =
         static_cast<mitk::DiffusionImage<DiffusionPixelType>*>(
         (*itemiter)->GetData());
 
       std::string nodename;
       (*itemiter)->GetStringProperty("name", nodename);
       ++itemiter;
 
       // TENSOR RECONSTRUCTION
       clock.Start();
       MBI_INFO << "Teem Tensor reconstruction ";
       mitk::StatusBar::GetInstance()->DisplayText(status.sprintf(
         "Teem Tensor reconstruction for %s", nodename.c_str()).toAscii());
       typedef mitk::TeemDiffusionTensor3DReconstructionImageFilter<
         DiffusionPixelType, TTensorPixelType > TensorReconstructionImageFilterType;
       TensorReconstructionImageFilterType::Pointer tensorReconstructionFilter =
         TensorReconstructionImageFilterType::New();
       tensorReconstructionFilter->SetInput( vols );
       if(!m_Controls->m_TensorEstimationTeemSigmaEdit->text().contains(QString("NaN")))
         tensorReconstructionFilter->SetSigma( m_Controls->m_TensorEstimationTeemSigmaEdit->text().toFloat() );
       switch(m_Controls->m_TensorEstimationTeemEstimationMethodCombo->currentIndex())
       {
         //  items << "LLS (Linear Least Squares)"
         //<< "MLE (Maximum Likelihood)"
         //<< "NLS (Nonlinear Least Squares)"
         //<< "WLS (Weighted Least Squares)";
       case 0:
         tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsLLS);
         break;
       case 1:
         tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsMLE);
         break;
       case 2:
         tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsNLS);
         break;
       case 3:
         tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsWLS);
         break;
       default:
         tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsLLS);
       }
       tensorReconstructionFilter->SetNumIterations( m_Controls->m_TensorEstimationTeemNumItsSpin->value() );
       if(m_Controls->m_TensorEstimationManualThreashold->isChecked())
         tensorReconstructionFilter->SetConfidenceThreshold( m_Controls->m_TensorReconstructionThreasholdEdit_2->text().toDouble() );
       tensorReconstructionFilter->SetConfidenceFuzzyness( m_Controls->m_TensorEstimationTeemFuzzyEdit->text().toFloat() );
       tensorReconstructionFilter->SetMinPlausibleValue( m_Controls->m_TensorEstimationTeemMinValEdit->text().toDouble() );
       tensorReconstructionFilter->Update();
       clock.Stop();
       MBI_DEBUG << "took " << clock.GetMeanTime() << "s." ;
 
       // TENSORS TO DATATREE
       mitk::DataNode::Pointer node2=mitk::DataNode::New();
       node2->SetData( tensorReconstructionFilter->GetOutputItk() );
 
       QString newname;
       newname = newname.append(nodename.c_str());
       newname = newname.append("_dtix");
 
       SetDefaultNodeProperties(node2, newname.toStdString());
       nodes.push_back(node2);
 
       mitk::ProgressBar::GetInstance()->Progress();
 
     }
 
     std::vector<mitk::DataNode::Pointer>::iterator nodeIt;
     for(nodeIt = nodes.begin(); nodeIt != nodes.end(); ++nodeIt)
       GetDefaultDataStorage()->Add(*nodeIt);
 
     mitk::StatusBar::GetInstance()->DisplayText(status.sprintf("Finished Processing %d Files", nrFiles).toAscii());
     m_MultiWidget->RequestUpdate();
 
   }
   catch (itk::ExceptionObject &ex)
   {
     MBI_INFO << ex ;
     return ;
   }
 }
 
 void QmitkTensorReconstructionView::SetDefaultNodeProperties(mitk::DataNode::Pointer node, std::string name)
 {
   node->SetProperty( "ShowMaxNumber", mitk::IntProperty::New( 500 ) );
   node->SetProperty( "Scaling", mitk::FloatProperty::New( 1.0 ) );
   node->SetProperty( "Normalization", mitk::OdfNormalizationMethodProperty::New());
   node->SetProperty( "ScaleBy", mitk::OdfScaleByProperty::New());
   node->SetProperty( "IndexParam1", mitk::FloatProperty::New(2));
   node->SetProperty( "IndexParam2", mitk::FloatProperty::New(1));
   node->SetProperty( "visible", mitk::BoolProperty::New( true ) );
   node->SetProperty( "VisibleOdfs", mitk::BoolProperty::New( false ) );
   node->SetProperty ("layer", mitk::IntProperty::New(100));
   node->SetProperty( "DoRefresh", mitk::BoolProperty::New( true ) );
   //node->SetProperty( "opacity", mitk::FloatProperty::New(1.0f) );
 
   node->SetProperty( "name", mitk::StringProperty::New(name) );
 }
 
 
 //node->SetProperty( "volumerendering", mitk::BoolProperty::New( false ) );
 //node->SetProperty( "use color", mitk::BoolProperty::New( true ) );
 //node->SetProperty( "texture interpolation", mitk::BoolProperty::New( true ) );
 //node->SetProperty( "reslice interpolation", mitk::VtkResliceInterpolationProperty::New() );
 //node->SetProperty( "layer", mitk::IntProperty::New(0));
 //node->SetProperty( "in plane resample extent by geometry", mitk::BoolProperty::New( false ) );
 //node->SetOpacity(1.0f);
 //node->SetColor(1.0,1.0,1.0);
 //node->SetVisibility(true);
 //node->SetProperty( "IsTensorVolume", mitk::BoolProperty::New( true ) );
 
 //mitk::LevelWindowProperty::Pointer levWinProp = mitk::LevelWindowProperty::New();
 //mitk::LevelWindow levelwindow;
 ////  levelwindow.SetAuto( image );
 //levWinProp->SetLevelWindow( levelwindow );
 //node->GetPropertyList()->SetProperty( "levelwindow", levWinProp );
 
 //// add a default rainbow lookup table for color mapping
 //if(!node->GetProperty("LookupTable"))
 //{
 //  mitk::LookupTable::Pointer mitkLut = mitk::LookupTable::New();
 //  vtkLookupTable* vtkLut = mitkLut->GetVtkLookupTable();
 //  vtkLut->SetHueRange(0.6667, 0.0);
 //  vtkLut->SetTableRange(0.0, 20.0);
 //  vtkLut->Build();
 //  mitk::LookupTableProperty::Pointer mitkLutProp = mitk::LookupTableProperty::New();
 //  mitkLutProp->SetLookupTable(mitkLut);
 //  node->SetProperty( "LookupTable", mitkLutProp );
 //}
 //if(!node->GetProperty("binary"))
 //  node->SetProperty( "binary", mitk::BoolProperty::New( false ) );
 
 //// add a default transfer function
 //mitk::TransferFunction::Pointer tf = mitk::TransferFunction::New();
 //node->SetProperty ( "TransferFunction", mitk::TransferFunctionProperty::New ( tf.GetPointer() ) );
 
 //// set foldername as string property
 //mitk::StringProperty::Pointer nameProp = mitk::StringProperty::New( name );
 //node->SetProperty( "name", nameProp );
 
 void QmitkTensorReconstructionView::TensorsToDWI()
 {
   if (m_CurrentSelection)
   {
     mitk::DataStorage::SetOfObjects::Pointer set =
       mitk::DataStorage::SetOfObjects::New();
 
     int at = 0;
     for (IStructuredSelection::iterator i = m_CurrentSelection->Begin();
       i != m_CurrentSelection->End();
       ++i)
     {
 
       if (mitk::DataNodeObject::Pointer nodeObj = i->Cast<mitk::DataNodeObject>())
       {
         mitk::DataNode::Pointer node = nodeObj->GetDataNode();
         if(QString("TensorImage").compare(node->GetData()->GetNameOfClass())==0)
         {
           set->InsertElement(at++, node);
         }
       }
     }
 
     DoTensorsToDWI(set);
   }
 }
 
 void QmitkTensorReconstructionView::TensorsToQbi()
 {
   std::vector<mitk::DataNode*> nodes = this->GetDataManagerSelection();
   for (int i=0; i<nodes.size(); i++)
   {
     mitk::DataNode::Pointer tensorImageNode = nodes.at(i);
     MITK_INFO << "starting Q-Ball estimation";
 
     typedef float                                       TTensorPixelType;
     typedef itk::DiffusionTensor3D< TTensorPixelType >  TensorPixelType;
     typedef itk::Image< TensorPixelType, 3 >            TensorImageType;
 
     TensorImageType::Pointer itkvol = TensorImageType::New();
     mitk::CastToItkImage<TensorImageType>(dynamic_cast<mitk::TensorImage*>(tensorImageNode->GetData()), itkvol);
 
     typedef itk::TensorImageToQBallImageFilter< TTensorPixelType, TTensorPixelType > FilterType;
     FilterType::Pointer filter = FilterType::New();
     filter->SetInput( itkvol );
     filter->Update();
 
     typedef itk::Vector<TTensorPixelType,QBALL_ODFSIZE>  OutputPixelType;
     typedef itk::Image<OutputPixelType,3>                OutputImageType;
 
     mitk::QBallImage::Pointer image = mitk::QBallImage::New();
     OutputImageType::Pointer outimg = filter->GetOutput();
     image->InitializeByItk( outimg.GetPointer() );
     image->SetVolume( outimg->GetBufferPointer() );
     mitk::DataNode::Pointer node = mitk::DataNode::New();
     node->SetData( image );
     QString newname;
     newname = newname.append(tensorImageNode->GetName().c_str());
     newname = newname.append("_qbi");
     node->SetName(newname.toAscii());
     GetDefaultDataStorage()->Add(node);
   }
 }
 
 void QmitkTensorReconstructionView::OnSelectionChanged( std::vector<mitk::DataNode*> nodes )
 {
   if ( !this->IsVisible() )
     return;
 
 }
 
 template<int ndirs>
 std::vector<itk::Vector<double,3> > QmitkTensorReconstructionView::MakeGradientList()
 {
   std::vector<itk::Vector<double,3> > retval;
   vnl_matrix_fixed<double, 3, ndirs>* U =
     itk::PointShell<ndirs, vnl_matrix_fixed<double, 3, ndirs> >::DistributePointShell();
 
   for(int i=0; i<ndirs;i++)
   {
     itk::Vector<double,3> v;
     v[0] = U->get(0,i); v[1] = U->get(1,i); v[2] = U->get(2,i);
     retval.push_back(v);
   }
   // Add 0 vector for B0
   itk::Vector<double,3> v;
   v.Fill(0.0);
   retval.push_back(v);
 
   return retval;
 }
 
 void QmitkTensorReconstructionView::DoTensorsToDWI
 (mitk::DataStorage::SetOfObjects::Pointer inImages)
 {
   try
   {
     itk::TimeProbe clock;
 
     int nrFiles = inImages->size();
     if (!nrFiles) return;
 
     QString status;
     mitk::ProgressBar::GetInstance()->AddStepsToDo(nrFiles);
 
     mitk::DataStorage::SetOfObjects::const_iterator itemiter( inImages->begin() );
     mitk::DataStorage::SetOfObjects::const_iterator itemiterend( inImages->end() );
 
     std::vector<mitk::DataNode::Pointer> nodes;
     while ( itemiter != itemiterend ) // for all items
     {
 
       std::string nodename;
       (*itemiter)->GetStringProperty("name", nodename);
 
       mitk::TensorImage* vol =
         static_cast<mitk::TensorImage*>((*itemiter)->GetData());
 
       ++itemiter;
 
       typedef float                                       TTensorPixelType;
       typedef itk::DiffusionTensor3D< TTensorPixelType >  TensorPixelType;
       typedef itk::Image< TensorPixelType, 3 >            TensorImageType;
 
 
       TensorImageType::Pointer itkvol = TensorImageType::New();
       mitk::CastToItkImage<TensorImageType>(vol, itkvol);
 
       typedef itk::TensorImageToDiffusionImageFilter<
         TTensorPixelType, DiffusionPixelType > FilterType;
 
       FilterType::GradientListType gradientList;
 
       switch(m_Controls->m_TensorsToDWINumDirsSelect->currentIndex())
       {
       case 0:
         gradientList = MakeGradientList<12>();
         break;
       case 1:
         gradientList = MakeGradientList<42>();
         break;
       case 2:
         gradientList = MakeGradientList<92>();
         break;
       case 3:
         gradientList = MakeGradientList<162>();
         break;
       case 4:
         gradientList = MakeGradientList<252>();
         break;
       case 5:
         gradientList = MakeGradientList<362>();
         break;
       case 6:
         gradientList = MakeGradientList<492>();
         break;
       case 7:
         gradientList = MakeGradientList<642>();
         break;
       case 8:
         gradientList = MakeGradientList<812>();
         break;
       case 9:
         gradientList = MakeGradientList<1002>();
         break;
       default:
         gradientList = MakeGradientList<92>();
 
       }
 
       double bVal = m_Controls->m_TensorsToDWIBValueEdit->text().toDouble();
 
       // DWI ESTIMATION
       clock.Start();
       MBI_INFO << "DWI Estimation ";
       mitk::StatusBar::GetInstance()->DisplayText(status.sprintf(
         "DWI Estimation for %s", nodename.c_str()).toAscii());
       FilterType::Pointer filter = FilterType::New();
       filter->SetInput( itkvol );
       filter->SetBValue(bVal);
       filter->SetGradientList(gradientList);
       //filter->SetNumberOfThreads(1);
       filter->Update();
       clock.Stop();
       MBI_DEBUG << "took " << clock.GetMeanTime() << "s.";
 
       itk::Vector<double,3> v;
       v[0] = 0; v[1] = 0; v[2] = 0;
       gradientList.push_back(v);
 
       // TENSORS TO DATATREE
       mitk::DiffusionImage<DiffusionPixelType>::Pointer image = mitk::DiffusionImage<DiffusionPixelType>::New();
       image->SetVectorImage( filter->GetOutput() );
       image->SetB_Value(bVal);
       image->SetDirections(gradientList);
       image->SetOriginalDirections(gradientList);
       image->InitializeFromVectorImage();
       mitk::DataNode::Pointer node=mitk::DataNode::New();
       node->SetData( image );
 
       mitk::DiffusionImageMapper<short>::SetDefaultProperties(node);
 
       QString newname;
       newname = newname.append(nodename.c_str());
       newname = newname.append("_dwi");
       node->SetName(newname.toAscii());
 
       nodes.push_back(node);
 
       mitk::ProgressBar::GetInstance()->Progress();
 
     }
 
     std::vector<mitk::DataNode::Pointer>::iterator nodeIt;
     for(nodeIt = nodes.begin(); nodeIt != nodes.end(); ++nodeIt)
       GetDefaultDataStorage()->Add(*nodeIt);
 
     mitk::StatusBar::GetInstance()->DisplayText(status.sprintf("Finished Processing %d Files", nrFiles).toAscii());
     m_MultiWidget->RequestUpdate();
 
   }
   catch (itk::ExceptionObject &ex)
   {
     MBI_INFO << ex ;
     return ;
   }
 }