void mitk::ToFImageDownsamplingFilter::ItkImageResampling( const itk::Image<TPixel,VImageDimension>* itkImage )
{
// declare typdef for itk image from input mitk image
typedef itk::Image< TPixel, VImageDimension > ItkImageType;
//declare itk filter related typedefs (transform type, interpolater, and size type)
typedef itk::ResampleImageFilter<ItkImageType,ItkImageType> ResamplerFilterType;
typedef itk::IdentityTransform<double, VImageDimension> TransformType;
typedef itk::NearestNeighborInterpolateImageFunction<ItkImageType, double > InterpolatorType;
typedef typename ItkImageType::SizeType::SizeValueType SizeValueType;
//instantiate filter related parameters
typename ResamplerFilterType::Pointer resampler = ResamplerFilterType::New();
typename TransformType::Pointer transform = TransformType::New();
typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
// establish size for downsampled image ( the result of this filter)
typename ItkImageType::SizeType inputSize = itkImage->GetLargestPossibleRegion().GetSize();
typename ItkImageType::SizeType size;
size[0] = static_cast< SizeValueType >( m_ResampledX );
size[1] = static_cast< SizeValueType >( m_ResampledY );
size[2] = static_cast< SizeValueType >( m_ResampledZ );
//establish spacing for new downsampled image ( resulting image)
const typename ItkImageType::SpacingType& inputSpacing = itkImage->GetSpacing();
typename ItkImageType::SpacingType outputSpacing;
outputSpacing[0] = inputSpacing[0] * ( inputSize[0]/ m_ResampledX );
outputSpacing[1] = inputSpacing[1] * ( inputSize[1]/ m_ResampledY );
outputSpacing[2] = inputSpacing[2] * ( inputSize[2]/ m_ResampledZ );
mitk::Vector3D mitkspacing;
mitkspacing[0] = outputSpacing[0];
mitkspacing[1] = outputSpacing[1];
mitkspacing[2] = outputSpacing[2];
mitk::Point3D mitkorig;
mitkorig[0] = itkImage->GetOrigin()[0];
mitkorig[1] = itkImage->GetOrigin()[1];
mitkorig[2] = 0.0;
// set filter parameters and update
transform->SetIdentity();
resampler->SetTransform(transform);
resampler->SetInterpolator(interpolator);
resampler->SetOutputSpacing(outputSpacing);
resampler->SetOutputOrigin(itkImage->GetOrigin());
resampler->SetSize(size);
resampler->SetInput(itkImage);
resampler->UpdateLargestPossibleRegion();
// Create mitk container for resulting image
mitk::Image::Pointer resultImage = ImageToImageFilter::GetOutput();
resultImage->SetSpacing(mitkspacing);
resultImage->SetOrigin(mitkorig);
// Cast itk image to mitk image
mitk::CastToMitkImage(resampler->GetOutput(), resultImage);
}
void WorkbenchUtils::resampleImageItk(itk::Image <PixelType, ImageDimension> *itkImage, Interpolator interpolType,
unsigned int *newDimensions, Image::Pointer outImage) {
typedef itk::Image <PixelType, ImageDimension> ImageType;
// get original image informations
const typename ImageType::RegionType &inputRegion = itkImage->GetLargestPossibleRegion();
const typename ImageType::SizeType &inputDimensions = inputRegion.GetSize();
const typename ImageType::SpacingType &inputSpacing = itkImage->GetSpacing();
// calculate spacing
double outputSpacing[ImageDimension];
itk::Size <ImageDimension> outputSize;
for (unsigned int i = 0; i < ImageDimension; ++i) {
outputSpacing[i] = inputSpacing[i] * (double) inputDimensions[i] / newDimensions[i];
outputSize[i] = newDimensions[i];
}
// transform
typedef itk::IdentityTransform<double, ImageDimension> TransformType;
typename TransformType::Pointer transform = TransformType::New();
transform->SetIdentity();
// interpolator typedefs
typedef double CoordinateType;
typedef itk::LinearInterpolateImageFunction <ImageType, CoordinateType> LinearInterpolatorType;
typedef itk::NearestNeighborInterpolateImageFunction <ImageType, CoordinateType> NearestNeighborInterpolatorType;
typedef itk::GaussianInterpolateImageFunction <ImageType, CoordinateType> GaussianInterpolatorType;
typedef itk::BSplineInterpolateImageFunction <ImageType, CoordinateType> BSplineInterpolatorType;
// set up the filter
typedef itk::ResampleImageFilter <ImageType, ImageType> ResampleFilterType;
typename ResampleFilterType::Pointer resampleFilter = ResampleFilterType::New();
resampleFilter->SetTransform(transform);
resampleFilter->SetOutputOrigin(itkImage->GetOrigin());
resampleFilter->SetOutputSpacing(outputSpacing);
resampleFilter->SetSize(outputSize);
switch (interpolType) {
case Interpolator::LINEAR: // the default;
resampleFilter->SetInterpolator(LinearInterpolatorType::New());
break;
case Interpolator::NEAREST_NEIGHBOR:
resampleFilter->SetInterpolator(NearestNeighborInterpolatorType::New());
break;
case Interpolator::GAUSSIAN:
resampleFilter->SetInterpolator(GaussianInterpolatorType::New());
break;
case Interpolator::BSPLINE:
resampleFilter->SetInterpolator(BSplineInterpolatorType::New());
break;
}
resampleFilter->SetInput(itkImage);
resampleFilter->UpdateLargestPossibleRegion();
// get the results and cast them back to mitk. return via out parameter.
outImage->InitializeByItk(resampleFilter->GetOutput());
CastToMitkImage(resampleFilter->GetOutput(), outImage);
}
itk::Object::Pointer QmitkTranslationTransformView::GetTransform2(itk::Image<TPixelType, VImageDimension>* /*itkImage1*/)
{
typedef typename itk::Image< TPixelType, VImageDimension > FixedImageType;
typedef typename itk::Image< TPixelType, VImageDimension > MovingImageType;
typedef itk::AffineTransform<double, VImageDimension> TransformType;
typename TransformType::Pointer transform = TransformType::New();
transform->SetIdentity();
m_TransformObject = transform;
return transform.GetPointer();
}
typename TImage::Pointer modelBasedImageToImageRegistration(std::string referenceFilename,
std::string targetFilename,
typename TStatisticalModelType::Pointer model,
std::string outputDfFilename,
unsigned numberOfIterations){
typedef itk::ImageFileReader<TImage> ImageReaderType;
typedef itk::InterpolatingStatisticalDeformationModelTransform<TRepresenter, double, VImageDimension> TransformType;
typedef itk::LBFGSOptimizer OptimizerType;
typedef itk::ImageRegistrationMethod<TImage, TImage> RegistrationFilterType;
typedef itk::WarpImageFilter< TImage, TImage, TVectorImage > WarperType;
typedef itk::LinearInterpolateImageFunction< TImage, double > InterpolatorType;
typename ImageReaderType::Pointer referenceReader = ImageReaderType::New();
referenceReader->SetFileName(referenceFilename.c_str());
referenceReader->Update();
typename TImage::Pointer referenceImage = referenceReader->GetOutput();
referenceImage->Update();
typename ImageReaderType::Pointer targetReader = ImageReaderType::New();
targetReader->SetFileName(targetFilename.c_str());
targetReader->Update();
typename TImage::Pointer targetImage = targetReader->GetOutput();
targetImage->Update();
// do the fitting
typename TransformType::Pointer transform = TransformType::New();
transform->SetStatisticalModel(model);
transform->SetIdentity();
// Setting up the fitting
OptimizerType::Pointer optimizer = OptimizerType::New();
optimizer->MinimizeOn();
optimizer->SetMaximumNumberOfFunctionEvaluations(numberOfIterations);
typedef IterationStatusObserver ObserverType;
ObserverType::Pointer observer = ObserverType::New();
optimizer->AddObserver( itk::IterationEvent(), observer );
typename TMetricType::Pointer metric = TMetricType::New();
typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
typename RegistrationFilterType::Pointer registration = RegistrationFilterType::New();
registration->SetInitialTransformParameters(transform->GetParameters());
registration->SetMetric(metric);
registration->SetOptimizer( optimizer );
registration->SetTransform( transform );
registration->SetInterpolator( interpolator );
registration->SetFixedImage( targetImage );
registration->SetFixedImageRegion(targetImage->GetBufferedRegion() );
registration->SetMovingImage( referenceImage );
try {
std::cout << "Performing registration... " << std::flush;
registration->Update();
std::cout << "[done]" << std::endl;
} catch ( itk::ExceptionObject& o ) {
std::cout << "caught exception " << o << std::endl;
}
typename TVectorImage::Pointer df = model->DrawSample(transform->GetCoefficients());
// write deformation field
if(outputDfFilename.size()>0){
typename itk::ImageFileWriter<TVectorImage>::Pointer df_writer = itk::ImageFileWriter<TVectorImage>::New();
df_writer->SetFileName(outputDfFilename);
df_writer->SetInput(df);
df_writer->Update();
}
// warp reference
std::cout << "Warping reference... " << std::flush;
typename WarperType::Pointer warper = WarperType::New();
warper->SetInput(referenceImage );
warper->SetInterpolator( interpolator );
warper->SetOutputSpacing( targetImage->GetSpacing() );
warper->SetOutputOrigin( targetImage->GetOrigin() );
warper->SetOutputDirection( targetImage->GetDirection() );
warper->SetDisplacementField( df );
warper->Update();
std::cout << "[done]" << std::endl;
return warper->GetOutput();
}
