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/*=========================================================================1
Program: Advanced Normalization Tools
Copyright (c) ConsortiumOfANTS. All rights reserved.
See accompanying COPYING.txt or
https://github.com/stnava/ANTs/blob/master/ANTSCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#include "antsUtilities.h"
#include <algorithm>
#include "ReadWriteData.h"
#include "itkPreservationOfPrincipalDirectionTensorReorientationImageFilter.h"
#include "itkImageRegionIteratorWithIndex.h"
#include "itkWarpTensorImageMultiTransformFilter.h"
#include "itkTransformFileReader.h"
#include "itkTransformFactory.h"
namespace ants
{
// entry point for the library; parameter 'args' is equivalent to 'argv' in (argc,argv) of commandline parameters to
// 'main()'
int
RebaseTensorImage(std::vector<std::string> args, std::ostream * /*out_stream = nullptr */)
{
// put the arguments coming in as 'args' into standard (argc,argv) format;
// 'args' doesn't have the command name as first, argument, so add it manually;
// 'args' may have adjacent arguments concatenated into one argument,
// which the parser should handle
args.insert(args.begin(), "RebaseTensorImage");
const int argc = args.size();
char ** argv = new char *[args.size() + 1];
for (unsigned int i = 0; i < args.size(); ++i)
{
// allocate space for the string plus a null character
argv[i] = new char[args[i].length() + 1];
std::strncpy(argv[i], args[i].c_str(), args[i].length());
// place the null character in the end
argv[i][args[i].length()] = '\0';
}
argv[argc] = nullptr;
// class to automatically cleanup argv upon destruction
class Cleanup_argv
{
public:
Cleanup_argv(char ** argv_, int argc_plus_one_)
: argv(argv_)
, argc_plus_one(argc_plus_one_)
{}
~Cleanup_argv()
{
for (unsigned int i = 0; i < argc_plus_one; ++i)
{
delete[] argv[i];
}
delete[] argv;
}
private:
char ** argv;
unsigned int argc_plus_one;
};
Cleanup_argv cleanup_argv(argv, argc + 1);
// antscout->set_stream( out_stream );
if (argc < 5)
{
std::cout << "Usage: " << argv[0] << " Dimension infile.nii outfile.nii <PHYSICAL/LOCAL/reference.nii.gz> "
<< std::endl;
if (argc >= 2 && (std::string(argv[1]) == std::string("--help") || std::string(argv[1]) == std::string("-h")))
{
return EXIT_SUCCESS;
}
return EXIT_FAILURE;
}
const int dim = std::stoi(argv[1]);
const char * const moving_image_filename = argv[2];
const char * const output_image_filename = argv[3];
if (dim != 3)
{
std::cout << "RebaseTensorImage only supports 3D image volumes" << std::endl;
return EXIT_FAILURE;
}
using PixelType = itk::DiffusionTensor3D<double>;
using TensorImageType = itk::Image<PixelType, 3>;
using ImageType = itk::Image<float, 3>;
// No reason to use log-euclidean space
TensorImageType::Pointer img_mov;
ReadTensorImage<TensorImageType>(img_mov, moving_image_filename, false);
TensorImageType::DirectionType::InternalMatrixType direction = img_mov->GetDirection().GetVnlMatrix();
direction.set_identity();
std::cout << "Transforming space of " << moving_image_filename;
// std::cout << i << " = " << argv[i-1] << std::endl;
char * convert = argv[4];
if (strcmp(convert, "PHYSICAL") == 0)
{
std::cout << " -> physical space";
direction = img_mov->GetDirection().GetVnlMatrix();
}
else if (strcmp(convert, "LOCAL") == 0)
{
std::cout << " -> local space";
direction = img_mov->GetDirection().GetTranspose();
}
else
{
std::cout << " -> " << convert << " space";
ImageType::Pointer target;
ReadImage<ImageType>(target, convert);
// converting from LOCAL to a reference LOCAL space
direction = target->GetDirection().GetTranspose() * img_mov->GetDirection().GetVnlMatrix();
}
// direction = direction.transpose(); // to accomodate for how
// eigenvectors are stored
std::cout << std::endl;
std::cout << "Final rebasing matrix: " << std::endl << direction << std::endl;
if (!direction.is_identity(0.00001))
{
itk::ImageRegionIteratorWithIndex<TensorImageType> it(img_mov, img_mov->GetLargestPossibleRegion());
while (!it.IsAtEnd())
{
/*
PixelType dt = it.Value();
PixelType::EigenValuesArrayType evalues;
PixelType::EigenVectorsMatrixType evectors;
dt.ComputeEigenAnalysis( evalues, evectors );
evectors = evectors * direction;
PixelType::EigenVectorsMatrixType emat;
emat.Fill( 0.0 );
for (unsigned int i=0; i<3; i++)
{
emat(i,i) = evalues[i];
}
PixelType::EigenVectorsMatrixType::InternalMatrixType matrixDT = evectors.GetTranspose() * emat.GetVnlMatrix() *
evectors.GetVnlMatrix();
*/
PixelType::EigenVectorsMatrixType::InternalMatrixType dt;
dt(0, 0) = it.Value()[0];
dt(0, 1) = dt(1, 0) = it.Value()[1];
dt(0, 2) = dt(2, 0) = it.Value()[2];
dt(1, 1) = it.Value()[3];
dt(1, 2) = dt(2, 1) = it.Value()[4];
dt(2, 2) = it.Value()[5];
if ((it.Value()[0] + it.Value()[3] + it.Value()[5]) > 0.00001)
{
PixelType::EigenVectorsMatrixType::InternalMatrixType matrixDT = direction * dt * direction.transpose();
PixelType outDT;
outDT[0] = matrixDT(0, 0);
outDT[1] = matrixDT(1, 0);
outDT[2] = matrixDT(2, 0);
outDT[3] = matrixDT(1, 1);
outDT[4] = matrixDT(2, 1);
outDT[5] = matrixDT(2, 2);
it.Set(outDT);
}
++it;
}
}
else
{
std::cout << "Identity transform detected.. image unmodified" << std::endl;
}
// No reason to use log-euclidean space here
WriteTensorImage<TensorImageType>(img_mov, output_image_filename, false);
return EXIT_SUCCESS;
}
} // namespace ants
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