+ // Warning
+ if (!std::numeric_limits<PixelType>::is_signed) {
+ if ((mInterpolatorName == "bspline") || (mInterpolatorName == "blut")) {
+ std::cerr << "Warning : input pixel type is not signed, use bspline interpolation at your own risk ..." << std::endl;
+ }
+ }
+
+ // Check options
+ if (mOutputSize.size() != dim) {
+ std::cerr << "Please set size with " << dim << " dimensions." << std::endl;
+ return;
+ }
+ if (mOutputSpacing.size() != dim) {
+ std::cerr << "Please set spacing with " << dim << " dimensions." << std::endl;
+ return;
+ }
+ mOutputOrigin.resize(dim);
+
+ if (mApplyGaussianFilterBefore && mSigma.size() != dim) {
+ std::cerr << "Please set sigma with " << dim << " dimensions." << std::endl;
+ return;
+ }
+
+ // Create Image Filter
+ typedef itk::ResampleImageFilter<InputImageType,InputImageType> FilterType;
+ typename FilterType::Pointer filter = FilterType::New();
+
+ // Instance of the transform object to be passed to the resample
+ // filter. By default, identity transform is applied
+ typedef itk::AffineTransform<double, InputImageType::ImageDimension> TransformType;
+ typename TransformType::Pointer transform = TransformType::New();
+ filter->SetTransform(transform);
+
+ // Set filter's parameters
+ SizeType outputSize;
+ SpacingType outputSpacing;
+ PointType outputOrigin;
+ for(unsigned int i=0; i<InputImageType::ImageDimension; i++) {
+ outputSize[i] = mOutputSize[i];
+ outputSpacing[i] = mOutputSpacing[i];
+ outputOrigin[i] = input->GetOrigin()[i];
+ }
+
+ filter->SetSize(outputSize);
+ filter->SetOutputSpacing(outputSpacing);
+ filter->SetOutputOrigin(outputOrigin);
+ filter->SetDefaultPixelValue(static_cast<PixelType>(mDefaultPixelValue));//DS TODO//JV comme ça?
+
+ // Select interpolator
+ if (mInterpolatorName == "nn") {
+ typedef itk::NearestNeighborInterpolateImageFunction<InputImageType, double> InterpolatorType;
+ typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
+ filter->SetInterpolator(interpolator);
+ } else {
+ if (mInterpolatorName == "linear") {
+ typedef itk::LinearInterpolateImageFunction<InputImageType, double> InterpolatorType;
+ typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
+ filter->SetInterpolator(interpolator);
+ } else {
+ if (mInterpolatorName == "windowed sinc") {
+ typedef itk::WindowedSincInterpolateImageFunction<InputImageType, 4> InterpolatorType;
+ typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
+ filter->SetInterpolator(interpolator);
+ } else {
+ if (mInterpolatorName == "bspline") {
+ typedef itk::BSplineInterpolateImageFunction<InputImageType, double> InterpolatorType;
+ typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
+ interpolator->SetSplineOrder(mBSplineOrder);
+ filter->SetInterpolator(interpolator);
+ } else {
+ if (mInterpolatorName == "blut") {
+ typedef itk::BSplineInterpolateImageFunctionWithLUT<InputImageType, double> InterpolatorType;
+ typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
+ interpolator->SetSplineOrder(mBSplineOrder);
+ interpolator->SetLUTSamplingFactor(mSamplingFactors[0]);
+ filter->SetInterpolator(interpolator);
+ } else {
+ std::cerr << "Sorry, I do not know the interpolator '" << mInterpolatorName
+ << "'. Known interpolators are : nn, linear, bspline, blut" << std::endl;
+ exit(0);
+ }
+ }
+ }
+ }
+ }
+
+ // Build initial Gaussian bluring (if needed)
+ typedef itk::RecursiveGaussianImageFilter<InputImageType, InputImageType> GaussianFilterType;
+ std::vector<typename GaussianFilterType::Pointer> gaussianFilters;
+ if (mApplyGaussianFilterBefore) {
+ for(unsigned int i=0; i<InputImageType::ImageDimension; i++) {
+ // Create filter
+ gaussianFilters.push_back(GaussianFilterType::New());
+ // Set options
+ gaussianFilters[i]->SetDirection(i);
+ gaussianFilters[i]->SetOrder(GaussianFilterType::ZeroOrder);
+ gaussianFilters[i]->SetNormalizeAcrossScale(false);
+ gaussianFilters[i]->SetSigma(mSigma[i]); // in millimeter !
+ // Set input
+ if (i==0) gaussianFilters[i]->SetInput(input);
+ else gaussianFilters[i]->SetInput(gaussianFilters[i-1]->GetOutput());
+ }
+ filter->SetInput(gaussianFilters[InputImageType::ImageDimension-1]->GetOutput());
+ } else {
+ filter->SetInput(input);
+ }
+
+ // Go !
+ try {
+ filter->Update();
+ } catch( itk::ExceptionObject & err ) {
+ std::cerr << "Error while filtering " << m_InputFilenames[0].c_str()
+ << " " << err << std::endl;
+ exit(0);
+ }
+
+ // Get result
+ typename InputImageType::Pointer outputImage = filter->GetOutput();
+
+ // Write/save results
+ this->SetNextOutput<InputImageType>(outputImage);