#include <istream>
#include <iterator>
#include <itkCenteredEuler3DTransform.h>
+#include <itkRecursiveGaussianImageFilter.h>
#include "clitkElastix.h"
+#include "clitkResampleImageWithOptionsFilter.h"
namespace clitk
{
reader->Update();
typename InputImageType::Pointer input= reader->GetOutput();
+ //Adaptative size, spacing origin (use previous clitkResampleImage)
+ if (m_ArgsInfo.adaptive_given) {
+ // Filter
+ typedef clitk::ResampleImageWithOptionsFilter<InputImageType, OutputImageType> ResampleImageFilterType;
+ typename ResampleImageFilterType::Pointer filter = ResampleImageFilterType::New();
+ filter->SetInput(input);
+
+ // Set Verbose
+ filter->SetVerboseOptions(m_ArgsInfo.verbose_flag);
+
+ // Set size / spacing
+ static const unsigned int dim = OutputImageType::ImageDimension;
+ typename OutputImageType::SpacingType spacing;
+ typename OutputImageType::SizeType size;
+ typename OutputImageType::PointType origin;
+ typename OutputImageType::DirectionType direction;
+
+ if (m_ArgsInfo.like_given) {
+ itk::ImageIOBase::Pointer header = clitk::readImageHeader(m_ArgsInfo.like_arg);
+ if (header) {
+ for(unsigned int i=0; i<dim; i++){
+ spacing[i] = header->GetSpacing(i);
+ size[i] = header->GetDimensions(i);
+ origin[i] = header->GetOrigin(i);
+ }
+ for(unsigned int i=0; i<dim; i++) {
+ for(unsigned int j=0;j<dim;j++) {
+ direction(i,j) = header->GetDirection(i)[j];
+ }
+ }
+ filter->SetOutputSpacing(spacing);
+ filter->SetOutputSize(size);
+ filter->SetOutputOrigin(origin);
+ filter->SetOutputDirection(direction);
+ }
+ else {
+ std::cerr << "*** Warning : I could not read '" << m_ArgsInfo.like_arg << "' ***" << std::endl;
+ exit(0);
+ }
+ }
+ else {
+ if (m_ArgsInfo.spacing_given == 1) {
+ filter->SetOutputIsoSpacing(m_ArgsInfo.spacing_arg[0]);
+ }
+ else if ((m_ArgsInfo.spacing_given != 0) && (m_ArgsInfo.size_given != 0)) {
+ std::cerr << "Error: use spacing or size, not both." << std::endl;
+ exit(0);
+ }
+ else if (m_ArgsInfo.spacing_given) {
+ if ((m_ArgsInfo.spacing_given != 0) && (m_ArgsInfo.spacing_given != dim)) {
+ std::cerr << "Error: spacing should have one or " << dim << " values." << std::endl;
+ exit(0);
+ }
+ for(unsigned int i=0; i<dim; i++)
+ spacing[i] = m_ArgsInfo.spacing_arg[i];
+ filter->SetOutputSpacing(spacing);
+ }
+ else if (m_ArgsInfo.size_given) {
+ if ((m_ArgsInfo.size_given != 0) && (m_ArgsInfo.size_given != dim)) {
+ std::cerr << "Error: size should have " << dim << " values." << std::endl;
+ exit(0);
+ }
+ for(unsigned int i=0; i<dim; i++)
+ size[i] = m_ArgsInfo.size_arg[i];
+ filter->SetOutputSize(size);
+ }
+ for(unsigned int i=0; i<dim; i++){
+ origin[i] = input->GetOrigin()[i];
+ }
+ for(unsigned int i=0; i<dim; i++) {
+ for(unsigned int j=0;j<dim;j++) {
+ direction(i,j) = input->GetDirection()[i][j];
+ }
+ }
+ filter->SetOutputOrigin(origin);
+ filter->SetOutputDirection(direction);
+ }
+
+ // Set temporal dimension
+ //filter->SetLastDimensionIsTime(m_ArgsInfo.time_flag);
+
+ // Set Gauss
+ filter->SetGaussianFilteringEnabled(m_ArgsInfo.autogauss_flag);
+ if (m_ArgsInfo.gauss_given != 0) {
+ typename ResampleImageFilterType::GaussianSigmaType g;
+ for(unsigned int i=0; i<dim; i++) {
+ g[i] = m_ArgsInfo.gauss_arg[i];
+ }
+ filter->SetGaussianSigma(g);
+ }
+
+ // Set Interpolation
+ int interp = m_ArgsInfo.interp_arg;
+ if (interp == 0) {
+ filter->SetInterpolationType(ResampleImageFilterType::NearestNeighbor);
+ } else {
+ if (interp == 1) {
+ filter->SetInterpolationType(ResampleImageFilterType::Linear);
+ } else {
+ if (interp == 2) {
+ filter->SetInterpolationType(ResampleImageFilterType::BSpline);
+ } else {
+ if (interp == 3) {
+ filter->SetInterpolationType(ResampleImageFilterType::B_LUT);
+ } else {
+ std::cerr << "Error. I do not know interpolation '" << m_ArgsInfo.interp_arg
+ << "'. Choose among: nn, linear, bspline, blut, windowed sinc" << std::endl;
+ exit(0);
+ }
+ }
+ }
+ }
+
+ // Set default pixel value
+ filter->SetDefaultPixelValue(m_ArgsInfo.pad_arg);
+
+ // Set thread
+ //if (m_ArgsInfo.thread_given) {
+ // filter->SetNumberOfThreads(m_ArgsInfo.thread_arg);
+ //}
+
+ // Go !
+ filter->Update();
+ typename OutputImageType::Pointer output = filter->GetOutput();
+ //this->template SetNextOutput<OutputImageType>(outputImage);
+
+ // Output
+ typedef itk::ImageFileWriter<OutputImageType> WriterType;
+ typename WriterType::Pointer writer = WriterType::New();
+ writer->SetFileName(m_ArgsInfo.output_arg);
+ writer->SetInput(output);
+ writer->Update();
+
+ return;
+ }
+
+ //Gaussian pre-filtering
+ typename itk::Vector<double, Dimension> gaussianSigma;
+ gaussianSigma.Fill(0);
+ bool gaussianFilteringEnabled(false);
+ bool autoGaussEnabled(false);
+ if (m_ArgsInfo.autogauss_given) { // Gaussian filter auto
+ autoGaussEnabled = m_ArgsInfo.autogauss_flag;
+ }
+ if (m_ArgsInfo.gauss_given) { // Gaussian filter set by user
+ gaussianFilteringEnabled = true;
+ if (m_ArgsInfo.gauss_given == 1)
+ {
+ for (unsigned int i=0; i<Dimension; i++)
+ {
+ gaussianSigma[i] = m_ArgsInfo.gauss_arg[0];
+ }
+ }
+ else if (m_ArgsInfo.gauss_given == Dimension)
+ {
+ for (unsigned int i=0; i<Dimension; i++)
+ {
+ gaussianSigma[i] = m_ArgsInfo.gauss_arg[i];
+ }
+ }
+ else
+ {
+ std::cerr << "Gaussian sigma dimension is incorrect" << std::endl;
+ return;
+ }
+ }
+
//Filter
typedef itk::ResampleImageFilter< InputImageType,OutputImageType > ResampleFilterType;
typename ResampleFilterType::Pointer resampler = ResampleFilterType::New();
likeReader->Update();
resampler->SetOutputParametersFromImage(likeReader->GetOutput());
resampler->SetOutputDirection(likeReader->GetOutput()->GetDirection());
+ if (autoGaussEnabled) { // Automated sigma when downsample
+ for(unsigned int i=0; i<Dimension; i++) {
+ if (likeReader->GetOutput()->GetSpacing()[i] > input->GetSpacing()[i]) { // downsample
+ gaussianSigma[i] = 0.5*likeReader->GetOutput()->GetSpacing()[i];// / inputSpacing[i]);
+ }
+ else gaussianSigma[i] = 0; // will be ignore after
+ }
+ }
} else if(m_ArgsInfo.transform_grid_flag) {
typename itk::Matrix<double, Dimension+1, Dimension+1> invMatrix( matrix.GetInverse() );
typename itk::Matrix<double, Dimension, Dimension> invRotMatrix( clitk::GetRotationalPartMatrix(invMatrix) );
outputSpacing = invRotMatrix *
input->GetDirection() *
input->GetSpacing();
+ if (autoGaussEnabled) { // Automated sigma when downsample
+ for(unsigned int i=0; i<Dimension; i++) {
+ if (outputSpacing[i] > input->GetSpacing()[i]) { // downsample
+ gaussianSigma[i] = 0.5*outputSpacing[i];// / inputSpacing[i]);
+ }
+ else gaussianSigma[i] = 0; // will be ignore after
+ }
+ }
// Origin is influenced by translation but not by input direction
typename InputImageType::PointType outputOrigin;
for(unsigned int i=0; i< Dimension; i++)
outputSpacing[i]=m_ArgsInfo.spacing_arg[i];
} else outputSpacing=input->GetSpacing();
+ if (autoGaussEnabled) { // Automated sigma when downsample
+ for(unsigned int i=0; i<Dimension; i++) {
+ if (outputSpacing[i] > input->GetSpacing()[i]) { // downsample
+ gaussianSigma[i] = 0.5*outputSpacing[i];// / inputSpacing[i]);
+ }
+ else gaussianSigma[i] = 0; // will be ignore after
+ }
+ }
//Origin
typename OutputImageType::PointType outputOrigin;
std::cout << "Setting the output direction to " << resampler->GetOutputDirection() << "..." << std::endl;
}
- resampler->SetInput( input );
+ typedef itk::RecursiveGaussianImageFilter<InputImageType, InputImageType> GaussianFilterType;
+ std::vector<typename GaussianFilterType::Pointer> gaussianFilters;
+ if (gaussianFilteringEnabled || autoGaussEnabled) {
+ for(unsigned int i=0; i<Dimension; i++) {
+ if (gaussianSigma[i] != 0) {
+ gaussianFilters.push_back(GaussianFilterType::New());
+ gaussianFilters[i]->SetDirection(i);
+ gaussianFilters[i]->SetOrder(GaussianFilterType::ZeroOrder);
+ gaussianFilters[i]->SetNormalizeAcrossScale(false);
+ gaussianFilters[i]->SetSigma(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) {
+ resampler->SetInput(gaussianFilters[gaussianFilters.size()-1]->GetOutput());
+ } else resampler->SetInput(input);
+ } else resampler->SetInput(input);
+
resampler->SetTransform( affineTransform );
resampler->SetInterpolator( genericInterpolator->GetInterpolatorPointer());
resampler->SetDefaultPixelValue( static_cast<PixelType>(m_ArgsInfo.pad_arg) );
reader->Update();
typename InputImageType::Pointer input= reader->GetOutput();
+ //Gaussian pre-filtering
+ typename itk::Vector<double, Dimension> gaussianSigma;
+ gaussianSigma.Fill(0);
+ bool gaussianFilteringEnabled(false);
+ bool autoGaussEnabled(false);
+ if (m_ArgsInfo.autogauss_given) { // Gaussian filter auto
+ autoGaussEnabled = m_ArgsInfo.autogauss_flag;
+ }
+ if (m_ArgsInfo.gauss_given) { // Gaussian filter set by user
+ gaussianFilteringEnabled = true;
+ if (m_ArgsInfo.gauss_given == 1)
+ {
+ for (unsigned int i=0; i<Dimension; i++)
+ {
+ gaussianSigma[i] = m_ArgsInfo.gauss_arg[0];
+ }
+ }
+ else if (m_ArgsInfo.gauss_given == Dimension)
+ {
+ for (unsigned int i=0; i<Dimension; i++)
+ {
+ gaussianSigma[i] = m_ArgsInfo.gauss_arg[i];
+ }
+ }
+ else
+ {
+ std::cerr << "Gaussian sigma dimension is incorrect" << std::endl;
+ return;
+ }
+ }
+
//Filter
typedef itk::VectorResampleImageFilter< InputImageType,OutputImageType, double > ResampleFilterType;
typename ResampleFilterType::Pointer resampler = ResampleFilterType::New();
resampler->SetOutputSpacing( likeReader->GetOutput()->GetSpacing() );
resampler->SetOutputOrigin( likeReader->GetOutput()->GetOrigin() );
resampler->SetOutputDirection( likeReader->GetOutput()->GetDirection() );
+ if (autoGaussEnabled) { // Automated sigma when downsample
+ for(unsigned int i=0; i<Dimension; i++) {
+ if (likeReader->GetOutput()->GetSpacing()[i] > input->GetSpacing()[i]) { // downsample
+ gaussianSigma[i] = 0.5*likeReader->GetOutput()->GetSpacing()[i];// / inputSpacing[i]);
+ }
+ else gaussianSigma[i] = 0; // will be ignore after
+ }
+ }
} else {
//Size
typename OutputImageType::SizeType outputSize;
for(unsigned int i=0; i< Dimension; i++)
outputSpacing[i]=m_ArgsInfo.spacing_arg[i];
} else outputSpacing=input->GetSpacing();
+ if (autoGaussEnabled) { // Automated sigma when downsample
+ for(unsigned int i=0; i<Dimension; i++) {
+ if (outputSpacing[i] > input->GetSpacing()[i]) { // downsample
+ gaussianSigma[i] = 0.5*outputSpacing[i];// / inputSpacing[i]);
+ }
+ else gaussianSigma[i] = 0; // will be ignore after
+ }
+ }
std::cout<<"Setting the spacing to "<<outputSpacing<<"..."<<std::endl;
//Origin
}
+ typedef itk::RecursiveGaussianImageFilter<InputImageType, InputImageType> GaussianFilterType;
+ std::vector<typename GaussianFilterType::Pointer> gaussianFilters;
+ if (gaussianFilteringEnabled || autoGaussEnabled) {
+ for(unsigned int i=0; i<Dimension; i++) {
+ if (gaussianSigma[i] != 0) {
+ gaussianFilters.push_back(GaussianFilterType::New());
+ gaussianFilters[i]->SetDirection(i);
+ gaussianFilters[i]->SetOrder(GaussianFilterType::ZeroOrder);
+ gaussianFilters[i]->SetNormalizeAcrossScale(false);
+ gaussianFilters[i]->SetSigma(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) {
+ resampler->SetInput(gaussianFilters[gaussianFilters.size()-1]->GetOutput());
+ } else resampler->SetInput(input);
+ } else resampler->SetInput(input);
+
resampler->SetInput( input );
resampler->SetTransform( affineTransform );
resampler->SetInterpolator( genericInterpolator->GetInterpolatorPointer());
git://git.creatis.insa-lyon.fr / clitk.git / blobdiff