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();
}
void SampleGradHistogram(double *pt, double radius, typename TImage::Pointer image, arma::ivec& samples)
{
typedef TImage ImageType;
int radius_pix[3]; //radius in voxels, to be calculated
radius_pix[0] = std::ceil(radius / image->GetSpacing()[0]);
radius_pix[1] = std::ceil(radius / image->GetSpacing()[1]);
radius_pix[2] = std::ceil(radius / image->GetSpacing()[2]);
#ifdef DEBUG_MESSAGES_HOG
std::cout << "Requested point: " << pt[0] << ", " << pt[1] << ", " << pt[2] << std::endl;
std::cout << "Neighborhood size in mm: " << radius << std::endl;
std::cout << "Neighborhood size in pix: " << radius_pix[0] << ", " << radius_pix[1] << ", " << radius_pix[2] << std::endl;
#endif
if (radius_pix[0] == 0 || radius_pix[1] == 0 || radius_pix[2] == 0) {
std::cout << "One of the neighborhood dimensions is zero. Please correct the radius. Aborting." << std::endl;
return;
}
//transform the point from physical s1pace
typename ImageType::PointType point;
point[0] = pt[0];
point[1] = pt[1];
point[2] = pt[2];
typename ImageType::IndexType pt_pix;
image->TransformPhysicalPointToIndex(point, pt_pix);
//define the region around the point of interest
typename ImageType::IndexType rgn_idx = {
{pt_pix[0] - radius_pix[0], pt_pix[1] - radius_pix[1], pt_pix[2] - radius_pix[2]}};
typename ImageType::SizeType rgn_size = {
{2 * radius_pix[0] + 1, 2 * radius_pix[1] + 1, 2 * radius_pix[2] + 1}};
//crop the region so that it is inside
rgn_idx[0] = std::max(rgn_idx[0], image->GetLargestPossibleRegion().GetIndex(0));
rgn_idx[1] = std::max(rgn_idx[1], image->GetLargestPossibleRegion().GetIndex(1));
rgn_idx[2] = std::max(rgn_idx[2], image->GetLargestPossibleRegion().GetIndex(2));
//set it first as a corner for comparison and then undo that operation
rgn_size[0] = std::min(rgn_size[0]+rgn_idx[0], image->GetLargestPossibleRegion().GetSize(0))-rgn_idx[0];
rgn_size[1] = std::min(rgn_size[1]+rgn_idx[1], image->GetLargestPossibleRegion().GetSize(1))-rgn_idx[1];
rgn_size[2] = std::min(rgn_size[2]+rgn_idx[2], image->GetLargestPossibleRegion().GetSize(2))-rgn_idx[2];
typename ImageType::RegionType window(rgn_idx, rgn_size);
#ifdef DEBUG_MESSAGES_HOG
std::cout << "Region: " << window << std::endl;
#endif
samples.set_size(rgn_size[0]*rgn_size[1]*rgn_size[2]);
samples.zeros();
// itk::ImageRegionConstIterator<typename GradientFilterType::OutputImageType> imageIterator(gradient_filter->GetOutput(), window);
itk::ImageRegionConstIterator<ImageType> imageIterator(image, window);
imageIterator.GoToBegin();
int i=0;
while (!imageIterator.IsAtEnd()) {
// Get the value of the current pixel
typename ImageType::PixelType val = imageIterator.Get();
//std::cout << val << std::endl;
samples[i++] = val;
++imageIterator;
}
}
void SampleStatistics(double *pt, double radius, typename TImage::Pointer image, arma::vec& features)
{
features.set_size(4); //just four features for now
features.zeros();
typedef TImage ImageType;
int radius_pix[3]; //radius in voxels, to be calculated
radius_pix[0] = std::ceil(radius / image->GetSpacing()[0]);
radius_pix[1] = std::ceil(radius / image->GetSpacing()[1]);
radius_pix[2] = std::ceil(radius / image->GetSpacing()[2]);
#ifdef DEBUG_MESSAGES_HOG
std::cout << "Requested point: " << pt[0] << ", " << pt[1] << ", " << pt[2] << std::endl;
std::cout << "Neighborhood size in mm: " << radius << std::endl;
std::cout << "Neighborhood size in pix: " << radius_pix[0] << ", " << radius_pix[1] << ", " << radius_pix[2] << std::endl;
#endif
if (radius_pix[0] == 0 || radius_pix[1] == 0 || radius_pix[2] == 0) {
std::cout << "One of the neighborhood dimensions is zero. Please correct the radius. Aborting." << std::endl;
return;
}
//transform the point from physical s1pace
typename ImageType::PointType point;
point[0] = pt[0];
point[1] = pt[1];
point[2] = pt[2];
typename ImageType::IndexType pt_pix;
image->TransformPhysicalPointToIndex(point, pt_pix);
//define the region around the point of interest
typename ImageType::IndexType rgn_idx = {
{pt_pix[0] - radius_pix[0], pt_pix[1] - radius_pix[1], pt_pix[2] - radius_pix[2]}};
typename ImageType::SizeType rgn_size = {
{2 * radius_pix[0] + 1, 2 * radius_pix[1] + 1, 2 * radius_pix[2] + 1}};
//crop the region so that it is inside
rgn_idx[0] = std::max(rgn_idx[0], image->GetLargestPossibleRegion().GetIndex(0));
rgn_idx[1] = std::max(rgn_idx[1], image->GetLargestPossibleRegion().GetIndex(1));
rgn_idx[2] = std::max(rgn_idx[2], image->GetLargestPossibleRegion().GetIndex(2));
//set it first as a corner for comparison and then undo that operation
rgn_size[0] = std::min(rgn_size[0]+rgn_idx[0], image->GetLargestPossibleRegion().GetSize(0))-rgn_idx[0];
rgn_size[1] = std::min(rgn_size[1]+rgn_idx[1], image->GetLargestPossibleRegion().GetSize(1))-rgn_idx[1];
rgn_size[2] = std::min(rgn_size[2]+rgn_idx[2], image->GetLargestPossibleRegion().GetSize(2))-rgn_idx[2];
typename ImageType::RegionType window(rgn_idx, rgn_size);
#ifdef DEBUG_MESSAGES_HOG
std::cout << "Region: " << window << std::endl;
#endif
itk::ImageRegionConstIterator<ImageType> imageIterator(image, window);
imageIterator.GoToBegin();
const int nvoxels = rgn_size[0]*rgn_size[1]*rgn_size[2];
arma::vec voxels;
voxels.set_size(nvoxels);
voxels.zeros();
long int i=0;
while (!imageIterator.IsAtEnd()) {
// Get the value of the current pixel
typename ImageType::PixelType val = imageIterator.Get();
//std::cout << val << std::endl;
voxels[i++] = val;
++imageIterator;
}
//do the statistics
const double mean = arma::mean(voxels);
const double std = arma::stddev(voxels);
double E3 = 0; //Accumulate expectation of (X-u)^3
double E4 = 0; //Accumulate expectation of (X-u)^4
for(int i=0; i<voxels.size(); i++)
{
const double diff = voxels[i] - mean;
const double k = diff*diff*diff/nvoxels;
E3 += k; //cubed
E4 += diff*k; //4th power
}
features[0] = mean;
features[1] = std;
features[2] = E3/(std*std*std); //skewness
features[3] = E3/(std*std*std*std); //kurtosis
}