X-Git-Url: https://git.creatis.insa-lyon.fr/pubgit/?a=blobdiff_plain;f=itk%2FclitkResampleImageWithOptionsFilter.txx;h=a3f88beb3db8443f08fa376da1480433f24e4051;hb=02f230e65dbfde06e84da374bb085643e29b5090;hp=aee15f5d397670e4f90a30c5b8ac497116bc2c20;hpb=8e4f61d01c82ffcf2e9180d7fd4e3aedac83f6f7;p=clitk.git

diff --git a/itk/clitkResampleImageWithOptionsFilter.txx b/itk/clitkResampleImageWithOptionsFilter.txx
index aee15f5..a3f88be 100644
--- a/itk/clitkResampleImageWithOptionsFilter.txx
+++ b/itk/clitkResampleImageWithOptionsFilter.txx
@@ -1,9 +1,9 @@
 /*=========================================================================
   Program:   vv                     http://www.creatis.insa-lyon.fr/rio/vv
 
-  Authors belong to: 
+  Authors belong to:
   - University of LYON              http://www.universite-lyon.fr/
-  - Léon Bérard cancer center       http://oncora1.lyon.fnclcc.fr
+  - Léon Bérard cancer center       http://www.centreleonberard.fr
   - CREATIS CNRS laboratory         http://www.creatis.insa-lyon.fr
 
   This software is distributed WITHOUT ANY WARRANTY; without even
@@ -14,10 +14,10 @@
 
   - BSD        See included LICENSE.txt file
   - CeCILL-B   http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
-  ======================================================================-====*/
+  ===========================================================================**/
 
 // clitk
-#include "clitkCommon.h"
+#include "clitkDD.h"
 
 // itk include
 #include "itkImage.h"
@@ -28,270 +28,307 @@
 #include "itkResampleImageFilter.h"
 #include "itkAffineTransform.h"
 #include "itkNearestNeighborInterpolateImageFunction.h"
+#include "itkWindowedSincInterpolateImageFunction.h"
 #include "itkLinearInterpolateImageFunction.h"
 #include "itkBSplineInterpolateImageFunction.h"
 #include "itkBSplineInterpolateImageFunctionWithLUT.h"
 #include "itkCommand.h"
 
-namespace clitk {
-
-  //--------------------------------------------------------------------
-  template <class TInputImage, class TOutputImage>
-  ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
-  ResampleImageWithOptionsFilter():itk::ImageToImageFilter<TInputImage, TOutputImage>() {
-    static const unsigned int dim = InputImageType::ImageDimension;
-    this->SetNumberOfRequiredInputs(1);
-    m_OutputIsoSpacing = -1;
-    m_InterpolationType = NearestNeighbor;
-    m_GaussianFilteringEnabled = true;
-    m_BSplineOrder = 3;
-    m_BLUTSamplingFactor = 20;
-    m_LastDimensionIsTime = false;
-    m_Transform =  TransformType::New();
-    if (dim == 4) m_LastDimensionIsTime = true; // by default 4D is 3D+t
-    for(unsigned int i=0; i<dim; i++) {
-      m_OutputSize[i] = 0;
-      m_OutputSpacing[i] = -1;
-      m_GaussianSigma[i] = -1;
-    }
-    m_VerboseOptions = false;
+//--------------------------------------------------------------------
+template <class InputImageType, class OutputImageType>
+clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
+ResampleImageWithOptionsFilter():itk::ImageToImageFilter<InputImageType, OutputImageType>() 
+{
+  static const unsigned int dim = InputImageType::ImageDimension;
+  this->SetNumberOfRequiredInputs(1);
+  m_OutputIsoSpacing = -1;
+  m_InterpolationType = NearestNeighbor;
+  m_GaussianFilteringEnabled = true;
+  m_BSplineOrder = 3;
+  m_BLUTSamplingFactor = 20;
+  m_LastDimensionIsTime = false;
+  m_Transform =  TransformType::New();
+  if (dim == 4) m_LastDimensionIsTime = true; // by default 4D is 3D+t
+  for(unsigned int i=0; i<dim; i++) {
+    m_OutputSize[i] = 0;
+    m_OutputSpacing[i] = -1;
+    m_GaussianSigma[i] = -1;
   }
-  //--------------------------------------------------------------------
+  m_VerboseOptions = false;
+  SetDefaultPixelValue(0);
+}
+//--------------------------------------------------------------------
 
 
-  //--------------------------------------------------------------------
-  template <class TInputImage, class TOutputImage>
-  void 
-  ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
-  SetInput(const InputImageType * image) {
-    // Process object is not const-correct so the const casting is required.
-    this->SetNthInput(0, const_cast<InputImageType *>(image));
-  }
-  //--------------------------------------------------------------------
-  
-
-  //--------------------------------------------------------------------
-  template <class TInputImage, class TOutputImage>
-  void 
-  ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
-  GenerateInputRequestedRegion() {
-    // call the superclass's implementation of this method
-    Superclass::GenerateInputRequestedRegion();
-    
-    // get pointers to the input and output
-    InputImagePointer  inputPtr  = 
-      const_cast< TInputImage *>( this->GetInput() );
-    
-    // Request the entire input image
-    InputImageRegionType inputRegion;
-    inputRegion = inputPtr->GetLargestPossibleRegion();
-    inputPtr->SetRequestedRegion(inputRegion);
-   }
-  //--------------------------------------------------------------------
-
-
-  //--------------------------------------------------------------------
-  template <class TInputImage, class TOutputImage>
-  void 
-  ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
-  GenerateOutputInformation() { 
-    static const unsigned int dim = InputImageType::ImageDimension;
-
-    // Warning
-    if (!std::numeric_limits<InputImagePixelType>::is_signed) {
-      if ((m_InterpolationType == BSpline) || 
-          (m_InterpolationType == B_LUT)) {
-        std::cerr << "Warning : input pixel type is not signed, use bspline interpolation at your own risk ..." << std::endl;
-      }
+//--------------------------------------------------------------------
+template <class InputImageType, class OutputImageType>
+void
+clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
+SetInput(const InputImageType * image) 
+{
+  // Process object is not const-correct so the const casting is required.
+  this->SetNthInput(0, const_cast<InputImageType *>(image));
+}
+//--------------------------------------------------------------------
+
+
+//--------------------------------------------------------------------
+template <class InputImageType, class OutputImageType>
+void
+clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
+GenerateInputRequestedRegion() 
+{
+  // call the superclass's implementation of this method
+  Superclass::GenerateInputRequestedRegion();
+
+  // get pointers to the input and output
+  InputImagePointer  inputPtr  =
+    const_cast< InputImageType *>( this->GetInput() );
+
+  // Request the entire input image
+  InputImageRegionType inputRegion;
+  inputRegion = inputPtr->GetLargestPossibleRegion();
+  inputPtr->SetRequestedRegion(inputRegion);
+}
+//--------------------------------------------------------------------
+
+
+//--------------------------------------------------------------------
+template <class InputImageType, class OutputImageType>
+void
+clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
+GenerateOutputInformation() 
+{
+  static const unsigned int dim = InputImageType::ImageDimension;
+
+  // Warning
+  if (!std::numeric_limits<InputImagePixelType>::is_signed) {
+    if ((m_InterpolationType == BSpline) ||
+        (m_InterpolationType == B_LUT)) {
+      std::cerr << "Warning : input pixel type is not signed, use bspline interpolation at your own risk ..." << std::endl;
     }
+  }
+
+  // Get input pointer
+  InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
 
-    // Get input pointer
-    InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
-     
-    // Perform default implementation
-    Superclass::GenerateOutputInformation();
+  // Perform default implementation
+  Superclass::GenerateOutputInformation();
 
-    // Compute sizes 
-    InputImageSpacingType inputSpacing = input->GetSpacing();
-    InputImageSizeType inputSize = input->GetLargestPossibleRegion().GetSize();
+  // Compute sizes
+  InputImageSpacingType inputSpacing = input->GetSpacing();
+  InputImageSizeType inputSize = input->GetLargestPossibleRegion().GetSize();
 
-    if (m_OutputIsoSpacing != -1) { // apply isoSpacing
+  if (m_OutputIsoSpacing != -1) { // apply isoSpacing
+    for(unsigned int i=0; i<dim; i++) {
+      m_OutputSpacing[i] = m_OutputIsoSpacing;
+      // floor() is used to intentionally reduce the number of slices 
+      // because, from a clinical point of view, it's better to 
+      // remove data than to add data that privously didn't exist.
+      if(inputSpacing[i]*m_OutputSpacing[i]<0)
+        itkExceptionMacro( << "Input and output spacings don't have the same signs, can't cope with that" );
+      m_OutputSize[i] = (int)floor(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
+    }
+  } else {
+    if (m_OutputSpacing[0] != -1) { // apply spacing, compute size
       for(unsigned int i=0; i<dim; i++) {
-        m_OutputSpacing[i] = m_OutputIsoSpacing;
-        m_OutputSize[i] = (int)lrint(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
+        if(inputSpacing[i]*m_OutputSpacing[i]<0)
+          itkExceptionMacro( << "Input and output spacings don't have the same signs, can't cope with that" );
+	// see comment above for the use of floor()
+	m_OutputSize[i] = (int)floor(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
       }
-    }
-    else {
-      if (m_OutputSpacing[0] != -1) { // apply spacing, compute size
+    } else {
+      if (m_OutputSize[0] != 0) { // apply size, compute spacing
         for(unsigned int i=0; i<dim; i++) {
-          m_OutputSize[i] = (int)lrint(inputSize[i]*inputSpacing[i]/m_OutputSpacing[i]);
-        }
-      }
-      else {
-        if (m_OutputSize[0] != 0) { // apply size, compute spacing
-          for(unsigned int i=0; i<dim; i++) {
-            m_OutputSpacing[i] = (double)inputSize[i]*inputSpacing[i]/(double)m_OutputSize[i];
-          }
-        }
-        else { // copy input size/spacing ... (no resampling)
-          m_OutputSize = inputSize;
-          m_OutputSpacing = inputSpacing;
+          m_OutputSpacing[i] = (double)inputSize[i]*inputSpacing[i]/(double)m_OutputSize[i];
         }
+      } else { // copy input size/spacing ... (no resampling)
+        m_OutputSize = inputSize;
+        m_OutputSpacing = inputSpacing;
       }
     }
+  }
 
-    // Special case for temporal image 2D+t or 3D+t
-    if (m_LastDimensionIsTime) {
-      int l = dim-1;
-      m_OutputSize[l] = inputSize[l];
-      m_OutputSpacing[l] = inputSpacing[l];
-    }
-    
-    // Set Size/Spacing
-    OutputImagePointer outputImage = this->GetOutput(0);
-    OutputImageRegionType region;
-    region.SetSize(m_OutputSize);
-    region.SetIndex(input->GetLargestPossibleRegion().GetIndex());
-    DD(input->GetLargestPossibleRegion().GetIndex());
-    outputImage->SetLargestPossibleRegion(region);
-    outputImage->SetSpacing(m_OutputSpacing);
-
-    // Init Gaussian sigma
-    if (m_GaussianSigma[0] != -1) { // Gaussian filter set by user
-      m_GaussianFilteringEnabled = true;
-    }
-    else {
-      if (m_GaussianFilteringEnabled) { // Automated sigma when downsample
-        for(unsigned int i=0; i<dim; i++) {
-          if (m_OutputSpacing[i] > inputSpacing[i]) { // downsample
-            m_GaussianSigma[i] = 0.5*m_OutputSpacing[i];// / inputSpacing[i]);
-          }
-          else m_GaussianSigma[i] = 0; // will be ignore after
+  // Special case for temporal image 2D+t or 3D+t
+  if (m_LastDimensionIsTime) {
+    int l = dim-1;
+    m_OutputSize[l] = inputSize[l];
+    m_OutputSpacing[l] = inputSpacing[l];
+  }
+
+  // Set Size/Spacing
+  OutputImagePointer outputImage = this->GetOutput(0);
+  // OutputImageRegionType region;
+  m_OutputRegion.SetSize(m_OutputSize);
+  m_OutputRegion.SetIndex(input->GetLargestPossibleRegion().GetIndex());
+  outputImage->CopyInformation(input);
+  outputImage->SetLargestPossibleRegion(m_OutputRegion);
+  outputImage->SetSpacing(m_OutputSpacing);
+
+  // Init Gaussian sigma
+  if (m_GaussianSigma[0] != -1) { // Gaussian filter set by user
+    m_GaussianFilteringEnabled = true;
+  }
+  else {
+    if (m_GaussianFilteringEnabled) { // Automated sigma when downsample
+      for(unsigned int i=0; i<dim; i++) {
+        if (m_OutputSpacing[i] > inputSpacing[i]) { // downsample
+          m_GaussianSigma[i] = 0.5*m_OutputSpacing[i];// / inputSpacing[i]);
         }
+        else m_GaussianSigma[i] = 0; // will be ignore after
       }
     }
-    if (m_GaussianFilteringEnabled && m_LastDimensionIsTime) {
-      m_GaussianSigma[dim-1] = 0;
-    }
   }
-  //--------------------------------------------------------------------
+  if (m_GaussianFilteringEnabled && m_LastDimensionIsTime) {
+    m_GaussianSigma[dim-1] = 0;
+  }
+}
+//--------------------------------------------------------------------
 
 
-  //--------------------------------------------------------------------
-   template <class TInputImage, class TOutputImage>
-  void 
-  ResampleImageWithOptionsFilter<TInputImage, TOutputImage>::
-  GenerateData() {
+//--------------------------------------------------------------------
+template <class InputImageType, class OutputImageType>
+void 
+clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType>::
+GenerateData() 
+{
    
-    // Get input pointer
-    InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
-    static const unsigned int dim = InputImageType::ImageDimension;
-
-     // Create main Resample Image Filter
-    typedef itk::ResampleImageFilter<InputImageType,OutputImageType> FilterType;
-    typename FilterType::Pointer filter = FilterType::New();
-    filter->GraftOutput(this->GetOutput());
-//     this->GetOutput()->Print(std::cout);
-//     this->GetOutput()->SetBufferedRegion(this->GetOutput()->GetLargestPossibleRegion());
-//     this->GetOutput()->Print(std::cout);
-
-    // Print options if needed
-    if (m_VerboseOptions) {
-      std::cout << "Output Spacing = " << m_OutputSpacing << std::endl
-                << "Output Size    = " << m_OutputSize << std::endl
-                << "Gaussian       = " << m_GaussianFilteringEnabled << std::endl;
-      if (m_GaussianFilteringEnabled) 
-        std::cout << "Sigma          = " << m_GaussianSigma << std::endl;
-      std::cout << "Interpol       = ";
-      switch (m_InterpolationType) {
-      case NearestNeighbor: std::cout << "NearestNeighbor" << std::endl; break;
-      case Linear:          std::cout << "Linear" << std::endl; break;
-      case BSpline:         std::cout << "BSpline " << m_BSplineOrder << std::endl; break;
-      case B_LUT:           std::cout << "B-LUT " << m_BSplineOrder << " " << m_BLUTSamplingFactor << std::endl; break;
-      }
-      std::cout << "Threads        = " << this->GetNumberOfThreads() << std::endl;
-      std::cout << "LastDimIsTime  = " << m_LastDimensionIsTime << std::endl;
-    }
+  // Get input pointer
+  InputImagePointer input = dynamic_cast<InputImageType*>(itk::ProcessObject::GetInput(0));
+  static const unsigned int dim = InputImageType::ImageDimension;
 
-    // Instance of the transform object to be passed to the resample
-    // filter. By default, identity transform is applied
-    filter->SetTransform(m_Transform);
-    filter->SetSize(m_OutputSize);
-    filter->SetOutputSpacing(m_OutputSpacing);
-    filter->SetOutputOrigin(input->GetOrigin());
-    filter->SetDefaultPixelValue(m_DefaultPixelValue);
-    filter->SetNumberOfThreads(this->GetNumberOfThreads()); 
+  // Create main Resample Image Filter
+  typedef itk::ResampleImageFilter<InputImageType,OutputImageType> FilterType;
+  typename FilterType::Pointer filter = FilterType::New();
+  filter->GraftOutput(this->GetOutput());
+  this->GetOutput()->SetBufferedRegion(this->GetOutput()->GetLargestPossibleRegion());
 
-    // Select interpolator
+  // Print options if needed
+  if (m_VerboseOptions) {
+    std::cout << "Output Spacing = " << m_OutputSpacing << std::endl
+              << "Output Size    = " << m_OutputSize << std::endl
+              << "Gaussian       = " << m_GaussianFilteringEnabled << std::endl;
+    if (m_GaussianFilteringEnabled)
+      std::cout << "Sigma          = " << m_GaussianSigma << std::endl;
+    std::cout << "Interpol       = ";
     switch (m_InterpolationType) {
-    case NearestNeighbor: 
-      {
-        typedef itk::NearestNeighborInterpolateImageFunction<InputImageType, double> InterpolatorType;     
-        typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
-        filter->SetInterpolator(interpolator);
-        break;
-      }
-    case Linear: 
-      {
-        typedef itk::LinearInterpolateImageFunction<InputImageType, double> InterpolatorType;     
-        typename InterpolatorType::Pointer interpolator =  InterpolatorType::New();
-        filter->SetInterpolator(interpolator);
-        break;
-      }
-    case BSpline: 
-      {
-        typedef itk::BSplineInterpolateImageFunction<InputImageType, double> InterpolatorType; 
-        typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
-        interpolator->SetSplineOrder(m_BSplineOrder);
-        filter->SetInterpolator(interpolator);
-      break;
-      }
-    case B_LUT: 
-      {
-        typedef itk::BSplineInterpolateImageFunctionWithLUT<InputImageType, double> InterpolatorType; 
-        typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
-        interpolator->SetSplineOrder(m_BSplineOrder);
-        interpolator->SetLUTSamplingFactor(m_BLUTSamplingFactor);
-        filter->SetInterpolator(interpolator);
-        break;
-      }
+    case NearestNeighbor: std::cout << "NearestNeighbor" << std::endl; break;
+    case Linear: std::cout << "Linear" << std::endl; break;
+    case BSpline: std::cout << "BSpline " << m_BSplineOrder << std::endl; break;
+    case B_LUT: std::cout << "B-LUT " << m_BSplineOrder << " " << m_BLUTSamplingFactor << std::endl; break;
+    case WSINC: std::cout << "Windowed Sinc" << std::endl; break;
     }
-    
-    // Initial Gaussian blurring if needed
-    typedef itk::RecursiveGaussianImageFilter<InputImageType, InputImageType> GaussianFilterType;
-    std::vector<typename GaussianFilterType::Pointer> gaussianFilters;
-    if (m_GaussianFilteringEnabled) {
-      for(unsigned int i=0; i<dim; i++) {
-        if (m_GaussianSigma[i] != 0) {
-          gaussianFilters.push_back(GaussianFilterType::New());
-          gaussianFilters[i]->SetDirection(i);
-          gaussianFilters[i]->SetOrder(GaussianFilterType::ZeroOrder);
-          gaussianFilters[i]->SetNormalizeAcrossScale(false);
-          gaussianFilters[i]->SetSigma(m_GaussianSigma[i]); // in millimeter !
-          if (gaussianFilters.size() == 1) { // first
-            gaussianFilters[0]->SetInput(input);
-          }
-          else {
-            gaussianFilters[i]->SetInput(gaussianFilters[i-1]->GetOutput());
-          }
+    std::cout << "Threads        = " << this->GetNumberOfThreads() << std::endl;
+    std::cout << "LastDimIsTime  = " << m_LastDimensionIsTime << std::endl;
+  }
+
+  // Instance of the transform object to be passed to the resample
+  // filter. By default, identity transform is applied
+  filter->SetTransform(m_Transform);
+  filter->SetSize(m_OutputSize);
+  filter->SetOutputSpacing(m_OutputSpacing);
+  filter->SetOutputOrigin(input->GetOrigin());
+  filter->SetDefaultPixelValue(m_DefaultPixelValue);
+  filter->SetNumberOfThreads(this->GetNumberOfThreads()); 
+  filter->SetOutputDirection(input->GetDirection()); // <-- NEEDED if we want to keep orientation (in case of PermutAxes for example)
+
+  // Select interpolator
+  switch (m_InterpolationType) {
+  case NearestNeighbor: {
+    typedef itk::NearestNeighborInterpolateImageFunction<InputImageType, double> InterpolatorType;
+    typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
+    filter->SetInterpolator(interpolator);
+    break;
+  }
+  case Linear: {
+    typedef itk::LinearInterpolateImageFunction<InputImageType, double> InterpolatorType;
+    typename InterpolatorType::Pointer interpolator =  InterpolatorType::New();
+    filter->SetInterpolator(interpolator);
+    break;
+  }
+  case BSpline: {
+    typedef itk::BSplineInterpolateImageFunction<InputImageType, double> InterpolatorType;
+    typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
+    interpolator->SetSplineOrder(m_BSplineOrder);
+    filter->SetInterpolator(interpolator);
+    break;
+  }
+  case B_LUT: {
+    typedef itk::BSplineInterpolateImageFunctionWithLUT<InputImageType, double> InterpolatorType;
+    typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
+    interpolator->SetSplineOrder(m_BSplineOrder);
+    interpolator->SetLUTSamplingFactor(m_BLUTSamplingFactor);
+    filter->SetInterpolator(interpolator);
+    break;
+  }
+  case WSINC: {
+    typedef itk::WindowedSincInterpolateImageFunction<InputImageType, 4> InterpolatorType;
+    typename InterpolatorType::Pointer interpolator =  InterpolatorType::New();
+    filter->SetInterpolator(interpolator);
+    break;
+  }
+  }
+
+  // Initial Gaussian blurring if needed
+  // TODO : replace by itk::DiscreteGaussianImageFilter for small sigma
+  typedef itk::RecursiveGaussianImageFilter<InputImageType, InputImageType> GaussianFilterType;
+  std::vector<typename GaussianFilterType::Pointer> gaussianFilters;
+  if (m_GaussianFilteringEnabled) {
+    for(unsigned int i=0; i<dim; i++) {
+      if (m_GaussianSigma[i] != 0) {
+        gaussianFilters.push_back(GaussianFilterType::New());
+        gaussianFilters[i]->SetDirection(i);
+        gaussianFilters[i]->SetOrder(GaussianFilterType::ZeroOrder);
+        gaussianFilters[i]->SetNormalizeAcrossScale(false);
+        gaussianFilters[i]->SetSigma(m_GaussianSigma[i]); // in millimeter !
+        if (gaussianFilters.size() == 1) { // first
+          gaussianFilters[0]->SetInput(input);
+        } else {
+          gaussianFilters[i]->SetInput(gaussianFilters[i-1]->GetOutput());
         }
       }
-      if (gaussianFilters.size() > 0) {
-        filter->SetInput(gaussianFilters[gaussianFilters.size()-1]->GetOutput());
-      }
-      else filter->SetInput(input);
     }
-    else filter->SetInput(input);
-
-    // Go ! 
-    filter->Update();
-    
-    // Set output
-    // DD("before Graft");
-    this->GraftOutput(filter->GetOutput());
-    // DD("after Graft");
+    if (gaussianFilters.size() > 0) {
+      filter->SetInput(gaussianFilters[gaussianFilters.size()-1]->GetOutput());
+    } else filter->SetInput(input);
+  } else filter->SetInput(input);
+
+  // Go !
+  filter->Update();
+
+  // Set output
+  // DD("before Graft");
+
+  //this->GraftOutput(filter->GetOutput());
+  this->SetNthOutput(0, filter->GetOutput());
+
+  // DD("after Graft");
+}
+//--------------------------------------------------------------------
+
+
+//--------------------------------------------------------------------
+template<class InputImageType>
+typename InputImageType::Pointer 
+clitk::ResampleImageSpacing(typename InputImageType::Pointer input, 
+                            typename InputImageType::SpacingType spacing, 
+                            int interpolationType)
+{
+  typedef clitk::ResampleImageWithOptionsFilter<InputImageType> ResampleFilterType;
+  typename ResampleFilterType::Pointer resampler = ResampleFilterType::New();
+  resampler->SetInput(input);
+  resampler->SetOutputSpacing(spacing);
+  typename ResampleFilterType::InterpolationTypeEnumeration inter=ResampleFilterType::NearestNeighbor;
+  switch(interpolationType) {
+  case 0: inter = ResampleFilterType::NearestNeighbor; break;
+  case 1: inter = ResampleFilterType::Linear; break;
+  case 2: inter = ResampleFilterType::BSpline; break;
+  case 3: inter = ResampleFilterType::B_LUT; break;
+  case 4: inter = ResampleFilterType::WSINC; break;
   }
-  //--------------------------------------------------------------------
-  
-}//end clitk
- 
+  resampler->SetInterpolationType(inter);
+  resampler->SetGaussianFilteringEnabled(true);
+  resampler->Update();
+  return resampler->GetOutput();
+}
+//--------------------------------------------------------------------