void invcondemonsforces(int nlhs,
mxArray *plhs[],
int nrhs,
const mxArray *prhs[])
{
typedef float PixelType;
typedef itk::Image< PixelType, Dimension > ImageType;
typedef float VectorComponentType;
typedef itk::Vector<VectorComponentType, Dimension> VectorPixelType;
typedef itk::Image<VectorPixelType, Dimension> DeformationFieldType;
typedef itk::ESMInvConDemonsRegistrationFunction
<ImageType,ImageType,DeformationFieldType> DemonsRegistrationFunctionType;
//boost::timer timer;
// Allocate images and deformation field
typename ImageType::Pointer fixedimage
= ImageType::New();
typename ImageType::Pointer movingimage
= ImageType::New();
typename ImageType::Pointer fw_weightimage
= ImageType::New();
typename DeformationFieldType::Pointer field
= DeformationFieldType::New();
typename ImageType::Pointer jacobianimage
= ImageType::New();
typename DeformationFieldType::Pointer inv_field
= DeformationFieldType::New();
typename DeformationFieldType::Pointer update
= DeformationFieldType::New();
typename DeformationFieldType::SpacingType spacing;
spacing.Fill( 1.0 );
typename DeformationFieldType::PointType origin;
origin.Fill( 0.0 );
typename DeformationFieldType::RegionType region;
typename DeformationFieldType::SizeType size;
typename DeformationFieldType::IndexType start;
unsigned int numPix(1u);
const MatlabPixelType * fixinptr = static_cast<const MatlabPixelType *>(mxGetData(prhs[0]));
const MatlabPixelType * movinptr = static_cast<const MatlabPixelType *>(mxGetData(prhs[1]));
const MatlabPixelType * fieldinptrs[Dimension];
const MatlabPixelType * inv_fieldinptrs[Dimension];
mwSize matlabdims[Dimension];
for (unsigned int d=0; d<Dimension; d++)
{
matlabdims[d]= mxGetDimensions(prhs[0])[d];
size[d] = matlabdims[d];
start[d] = 0;
numPix *= size[d];
fieldinptrs[d] = static_cast<const MatlabPixelType *>(mxGetData(prhs[2+d]));
inv_fieldinptrs[d] = static_cast<const MatlabPixelType *>(mxGetData(prhs[2+Dimension+d]));
}
const MatlabPixelType * jacobianptr = static_cast<const MatlabPixelType *> (mxGetData(prhs[2*Dimension + 2]));
const MatlabPixelType * fw_weightptr = static_cast<const MatlabPixelType *> (mxGetData(prhs[2*Dimension + 3]));
const double RegWeight = static_cast<double>( mxGetPr(prhs[2*Dimension+4])[0] );
const unsigned int UseJacFlag = 1;
//std::cout << "RegWeight : " << RegWeight << std::endl;
region.SetSize( size );
region.SetIndex( start );
fixedimage->SetOrigin( origin );
fixedimage->SetSpacing( spacing );
fixedimage->SetRegions( region );
fixedimage->Allocate();
movingimage->SetOrigin( origin );
movingimage->SetSpacing( spacing );
movingimage->SetRegions( region );
movingimage->Allocate();
fw_weightimage->SetOrigin( origin );
fw_weightimage->SetSpacing( spacing );
fw_weightimage->SetRegions( region );
fw_weightimage->Allocate();
field->SetOrigin( origin );
field->SetSpacing( spacing );
field->SetRegions( region );
field->Allocate();
inv_field->SetOrigin( origin );
inv_field->SetSpacing( spacing );
inv_field->SetRegions( region );
inv_field->Allocate();
update->SetOrigin( origin );
update->SetSpacing( spacing );
update->SetRegions( region );
update->Allocate();
if (UseJacFlag > 0)
{
jacobianimage->SetOrigin( origin );
jacobianimage->SetSpacing( spacing );
jacobianimage->SetRegions( region );
jacobianimage->Allocate();
}
//mexPrintf("done Allocate(); %f sec\n", timer.elapsed());
//timer.restart();
PixelType * fixptr = fixedimage->GetBufferPointer();
const PixelType * const fixbuff_end = fixptr + numPix;
PixelType * movptr = movingimage->GetBufferPointer();
PixelType * fwweightptr = NULL;
PixelType * jacptr = NULL;
if (UseJacFlag > 0)
{
jacptr = jacobianimage->GetBufferPointer();
}
fwweightptr = fw_weightimage->GetBufferPointer();
VectorPixelType * fieldptr = field->GetBufferPointer();
VectorPixelType * inv_fieldptr = inv_field->GetBufferPointer();
while ( fixptr != fixbuff_end )
{
*fixptr++ = *fixinptr++;
*movptr++ = *movinptr++;
*fwweightptr++ = *fw_weightptr++;
for (unsigned int d=0; d<Dimension; d++)
{
(*fieldptr)[d] = *(fieldinptrs[d])++;
}
if (UseJacFlag > 0)
{
*jacptr++ = *jacobianptr++;
}
++fieldptr;
for (unsigned int d=0; d<Dimension; d++)
{
(*inv_fieldptr)[d] = *(inv_fieldinptrs[d])++;
}
++inv_fieldptr;
}
// Create demons function
typename DemonsRegistrationFunctionType::Pointer drfp
= DemonsRegistrationFunctionType::New();
//mexPrintf("step size: %f\n",mxGetPr(prhs[2*Dimension+2])[0]);
//drfp->SetMaximumUpdateStepLength( mxGetPr(prhs[2*Dimension+2])[0] );
typename DemonsRegistrationFunctionType::GradientType gtype = DemonsRegistrationFunctionType::Symmetric;
drfp->SetUseGradientType( gtype );
drfp->SetDeformationField( field );
drfp->SetInvDeformationField( inv_field);
drfp->SetFixedImage( fixedimage );
drfp->SetMovingImage( movingimage );
drfp->SetRegWeight(RegWeight);
drfp->SetUseFwWeight(true);
drfp->SetFwWeightImage(fw_weightimage);
if (UseJacFlag > 0)
{
drfp->SetUseJacobian(true);
drfp->SetJacobianDetImage(jacobianimage);
}
else
{
drfp->SetUseJacobian(false);
}
drfp->InitializeIteration();
//mexPrintf("done demons function init %f sec\n", timer.elapsed());
//timer.restart();
const itk::Size<Dimension> radius = drfp->GetRadius();
// Break the input into a series of regions. The first region is free
// of boundary conditions, the rest with boundary conditions. We operate
// on the output region because input has been copied to output.
typedef itk::NeighborhoodAlgorithm::ImageBoundaryFacesCalculator
<DeformationFieldType> FaceCalculatorType;
typedef typename FaceCalculatorType::FaceListType FaceListType;
typedef typename DemonsRegistrationFunctionType::NeighborhoodType
NeighborhoodIteratorType;
typedef itk::ImageRegionIterator<DeformationFieldType> UpdateIteratorType;
FaceCalculatorType faceCalculator;
FaceListType faceList = faceCalculator(field, region, radius);
typename FaceListType::iterator fIt = faceList.begin();
// Ask the function object for a pointer to a data structure it
// will use to manage any global values it needs. We'll pass this
// back to the function object at each calculation and then
// again so that the function object can use it to determine a
// time step for this iteration.
void * globalData = drfp->GetGlobalDataPointer();
// Process the non-boundary region.
NeighborhoodIteratorType nD(radius, field, *fIt);
UpdateIteratorType nU(update, *fIt);
nD.GoToBegin();
while( !nD.IsAtEnd() )
{
nU.Value() = drfp->ComputeUpdate(nD, globalData);
++nD;
++nU;
}
// Process each of the boundary faces.
NeighborhoodIteratorType bD;
UpdateIteratorType bU;
for (++fIt; fIt != faceList.end(); ++fIt)
{
bD = NeighborhoodIteratorType(radius, field, *fIt);
bU = UpdateIteratorType(update, *fIt);
bD.GoToBegin();
bU.GoToBegin();
while ( !bD.IsAtEnd() )
{
bU.Value() = drfp->ComputeUpdate(bD, globalData);
++bD;
++bU;
}
}
// Ask the finite difference function to compute the time step for
// this iteration. We give it the global data pointer to use, then
// ask it to free the global data memory.
//timeStep = df->ComputeGlobalTimeStep(globalData);
drfp->ReleaseGlobalDataPointer(globalData);
//mexPrintf("done actual computations %f sec\n", timer.elapsed());
//timer.restart();
// Allocate outputs
const mxClassID classID = mxGetClassID(prhs[0]);
MatlabPixelType * outptrs[Dimension];
for (unsigned int d=0; d<Dimension; d++)
{
plhs[d] = mxCreateNumericArray(
Dimension, matlabdims, classID, mxREAL);
outptrs[d] = static_cast<MatlabPixelType *>(mxGetData(plhs[d]));
}
//mexPrintf("done allocate outputs %f sec\n", timer.elapsed());
//timer.restart();
// put result into outputs
const VectorPixelType * upptr = update->GetBufferPointer();
const VectorPixelType * const upbuff_end = upptr + numPix;
while ( upptr != upbuff_end )
{
for (unsigned int d=0; d<Dimension; d++)
{
*(outptrs[d])++ = (*upptr)[d];
}
++upptr;
}
//mexPrintf("done outputs copy %f sec\n", timer.elapsed());
}
void BSplineRegistration::GenerateData2( itk::Image<TPixel, VImageDimension>* itkImage1)
{
std::cout << "start bspline registration" << std::endl;
// Typedefs
typedef typename itk::Image< TPixel, VImageDimension > InternalImageType;
typedef typename itk::Vector< float, VImageDimension > VectorPixelType;
typedef typename itk::Image< VectorPixelType, VImageDimension > DeformationFieldType;
typedef itk::BSplineDeformableTransform<
double,
VImageDimension,
3 > TransformType;
typedef typename TransformType::ParametersType ParametersType;
//typedef itk::LBFGSOptimizer OptimizerType;
typedef itk::SingleValuedNonLinearOptimizer OptimizerType;
//typedef itk::SingleValuedCostFunction MetricType;
typedef itk::MattesMutualInformationImageToImageMetric<
InternalImageType,
InternalImageType > MetricType;
typedef itk::MeanSquaresImageToImageMetric<
InternalImageType,
InternalImageType > MetricTypeMS;
typedef itk::LinearInterpolateImageFunction<
InternalImageType,
double > InterpolatorType;
typedef itk::ImageRegistrationMethod<
InternalImageType,
InternalImageType > RegistrationType;
typedef typename itk::WarpImageFilter<
InternalImageType,
InternalImageType,
DeformationFieldType > WarperType;
typedef typename TransformType::SpacingType SpacingType;
typedef typename TransformType::OriginType OriginType;
typedef itk::ResampleImageFilter<
InternalImageType,
InternalImageType > ResampleFilterType;
typedef itk::Image< TPixel, VImageDimension > OutputImageType;
// Sample new image with the same image type as the fixed image
typedef itk::CastImageFilter<
InternalImageType,
InternalImageType > CastFilterType;
typedef itk::Vector< float, VImageDimension > VectorType;
typedef itk::Image< VectorType, VImageDimension > DeformationFieldType;
typedef itk::BSplineDeformableTransformInitializer <
TransformType,
InternalImageType > InitializerType;
typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
typename RegistrationType::Pointer registration = RegistrationType::New();
typename InitializerType::Pointer initializer = InitializerType::New();
typename TransformType::Pointer transform = TransformType::New();
if(m_Metric==0 || m_Metric==1)
{
typename MetricType::Pointer metric = MetricType::New();
metric->SetNumberOfHistogramBins( 32);
metric->SetNumberOfSpatialSamples(90000);
registration->SetMetric( metric );
}
else{
typename MetricTypeMS::Pointer metric = MetricTypeMS::New();
registration->SetMetric( metric );
}
typename OptimizerFactory::Pointer optFac = OptimizerFactory::New();
optFac->SetOptimizerParameters(m_OptimizerParameters);
optFac->SetNumberOfTransformParameters(transform->GetNumberOfParameters());
OptimizerType::Pointer optimizer = optFac->GetOptimizer();
optimizer->AddObserver(itk::AnyEvent(), m_Observer);
//typedef mitk::MetricFactory <TPixel, VImageDimension> MetricFactoryType;
//typename MetricFactoryType::Pointer metricFac = MetricFactoryType::New();
//metricFac->SetMetricParameters(m_MetricParameters);
////MetricType::Pointer metric = metricFac->GetMetric();
typename InternalImageType::Pointer fixedImage = InternalImageType::New();
mitk::CastToItkImage(m_ReferenceImage, fixedImage);
typename InternalImageType::Pointer movingImage = itkImage1;
typename InternalImageType::RegionType fixedRegion = fixedImage->GetBufferedRegion();
typename InternalImageType::RegionType movingRegion = movingImage->GetBufferedRegion();
if(m_MatchHistograms)
{
typedef itk::RescaleIntensityImageFilter<InternalImageType,InternalImageType> FilterType;
typedef itk::HistogramMatchingImageFilter<InternalImageType,InternalImageType> HEFilterType;
typename FilterType::Pointer inputRescaleFilter = FilterType::New();
typename FilterType::Pointer referenceRescaleFilter = FilterType::New();
referenceRescaleFilter->SetInput(fixedImage);
inputRescaleFilter->SetInput(movingImage);
TPixel desiredMinimum = 0;
TPixel desiredMaximum = 255;
referenceRescaleFilter->SetOutputMinimum( desiredMinimum );
referenceRescaleFilter->SetOutputMaximum( desiredMaximum );
referenceRescaleFilter->UpdateLargestPossibleRegion();
inputRescaleFilter->SetOutputMinimum( desiredMinimum );
inputRescaleFilter->SetOutputMaximum( desiredMaximum );
inputRescaleFilter->UpdateLargestPossibleRegion();
// Histogram match the images
typename HEFilterType::Pointer intensityEqualizeFilter = HEFilterType::New();
intensityEqualizeFilter->SetReferenceImage( inputRescaleFilter->GetOutput() );
intensityEqualizeFilter->SetInput( referenceRescaleFilter->GetOutput() );
intensityEqualizeFilter->SetNumberOfHistogramLevels( 64 );
intensityEqualizeFilter->SetNumberOfMatchPoints( 12 );
intensityEqualizeFilter->ThresholdAtMeanIntensityOn();
intensityEqualizeFilter->Update();
//fixedImage = referenceRescaleFilter->GetOutput();
//movingImage = IntensityEqualizeFilter->GetOutput();
fixedImage = intensityEqualizeFilter->GetOutput();
movingImage = inputRescaleFilter->GetOutput();
}
//
registration->SetOptimizer( optimizer );
registration->SetInterpolator( interpolator );
registration->SetFixedImage( fixedImage );
registration->SetMovingImage( movingImage );
registration->SetFixedImageRegion(fixedRegion );
initializer->SetTransform(transform);
initializer->SetImage(fixedImage);
initializer->SetNumberOfGridNodesInsideTheImage( m_NumberOfGridPoints );
initializer->InitializeTransform();
registration->SetTransform( transform );
const unsigned int numberOfParameters = transform->GetNumberOfParameters();
typename itk::BSplineDeformableTransform<
double,
VImageDimension,
3 >::ParametersType parameters;
parameters.set_size(numberOfParameters);
parameters.Fill( 0.0 );
transform->SetParameters( parameters );
// We now pass the parameters of the current transform as the initial
// parameters to be used when the registration process starts.
registration->SetInitialTransformParameters( transform->GetParameters() );
std::cout << "Intial Parameters = " << std::endl;
std::cout << transform->GetParameters() << std::endl;
std::cout << std::endl << "Starting Registration" << std::endl;
try
{
double tstart(clock());
registration->StartRegistration();
double time = clock() - tstart;
time = time / CLOCKS_PER_SEC;
MITK_INFO << "Registration time: " << time;
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
}
typename OptimizerType::ParametersType finalParameters =
registration->GetLastTransformParameters();
std::cout << "Last Transform Parameters" << std::endl;
std::cout << finalParameters << std::endl;
transform->SetParameters( finalParameters );
/*
ResampleFilterType::Pointer resampler = ResampleFilterType::New();
resampler->SetTransform( transform );
resampler->SetInput( movingImage );
resampler->SetSize( fixedImage->GetLargestPossibleRegion().GetSize() );
resampler->SetOutputOrigin( fixedImage->GetOrigin() );
resampler->SetOutputSpacing( fixedImage->GetSpacing() );
resampler->SetOutputDirection( fixedImage->GetDirection() );
resampler->SetDefaultPixelValue( 100 );
resampler->SetInterpolator( interpolator);
resampler->Update();*/
// Generate deformation field
typename DeformationFieldType::Pointer field = DeformationFieldType::New();
field->SetRegions( movingRegion );
field->SetOrigin( movingImage->GetOrigin() );
field->SetSpacing( movingImage->GetSpacing() );
field->SetDirection( movingImage->GetDirection() );
field->Allocate();
typedef itk::ImageRegionIterator< DeformationFieldType > FieldIterator;
FieldIterator fi( field, movingRegion );
fi.GoToBegin();
typename TransformType::InputPointType fixedPoint;
typename TransformType::OutputPointType movingPoint;
typename DeformationFieldType::IndexType index;
VectorType displacement;
while( ! fi.IsAtEnd() )
{
index = fi.GetIndex();
field->TransformIndexToPhysicalPoint( index, fixedPoint );
movingPoint = transform->TransformPoint( fixedPoint );
displacement = movingPoint - fixedPoint;
fi.Set( displacement );
++fi;
}
// Use the deformation field to warp the moving image
typename WarperType::Pointer warper = WarperType::New();
warper->SetInput( movingImage );
warper->SetInterpolator( interpolator );
warper->SetOutputSpacing( movingImage->GetSpacing() );
warper->SetOutputOrigin( movingImage->GetOrigin() );
warper->SetOutputDirection( movingImage->GetDirection() );
warper->SetDeformationField( field );
warper->Update();
typename InternalImageType::Pointer result = warper->GetOutput();
if(m_UpdateInputImage)
{
Image::Pointer outputImage = this->GetOutput();
mitk::CastToMitkImage( result, outputImage );
}
// Save the deformationfield resulting from the registration
if(m_SaveDeformationField)
{
typedef itk::ImageFileWriter< DeformationFieldType > FieldWriterType;
typename FieldWriterType::Pointer fieldWriter = FieldWriterType::New();
fieldWriter->SetInput( field );
fieldWriter->SetFileName( m_DeformationFileName );
try
{
fieldWriter->Update();
}
catch( itk::ExceptionObject & excp )
{
std::cerr << "Exception thrown " << std::endl;
std::cerr << excp << std::endl;
//return EXIT_FAILURE;
}
}
}
void readwarpfile(int nlhs,
mxArray *plhs[],
int nrhs,
const mxArray *prhs[])
{
typedef int PixelType;
typedef itk::Image< PixelType, Dimension > ImageType;
// mexPrintf("the dimentsion is ", Dimension);
// typedef PixelType;
typedef itk::Vector<PixelType, Dimension> VectorPixelType;
typedef itk::Image<VectorPixelType, Dimension> DeformationFieldType;
typedef itk::WarpImageFilter
<ImageType, ImageType, DeformationFieldType> WarperType;
mexPrintf("input number is: %d", nrhs);
mexPrintf("output parameternumber is: %d", nlhs);
// mexPrintf("the dimentsion is :%d", Dimension);
//boost::timer timer;
typename DeformationFieldType::SizeType size;
typename DeformationFieldType::IndexType start;
unsigned int numPix(1u);
char * inputDfFilename;
mwSize matlabdims[Dimension];
// here, we should read image parameter
for (unsigned int d=0; d<Dimension; d++)
{
matlabdims[d]= mxGetDimensions(prhs[1])[d];
size[d] = matlabdims[d];
start[d] = 0;
numPix *= size[d];
// inptrs[d] = static_cast<const MatlabPixelType *>(mxGetData(prhs[d]));
}
inputDfFilename = mxArrayToString(prhs[0]);
mexPrintf("output file name is %s", inputDfFilename);
typename itk::ImageFileReader<DeformationFieldType>::Pointer df_reader = itk::ImageFileReader<DeformationFieldType>::New();
df_reader->SetFileName(inputDfFilename);
df_reader->Update();
// Allocate images and deformation field
typename ImageType::Pointer image
= ImageType::New();
typename DeformationFieldType::Pointer field = DeformationFieldType::New();
// typename DeformationFieldType::Pointer field = 0;
typename DeformationFieldType::SpacingType spacing;
spacing.Fill( 1.0 );
typename DeformationFieldType::PointType origin;
origin.Fill( 0.0 );
typename DeformationFieldType::RegionType region;
field = df_reader->GetOutput();
region = field->GetLargestPossibleRegion();
// initialize output point
const mxClassID classID = mxGetClassID(prhs[1]);
MatlabPixelType * fieldoutptrs[Dimension];
for (unsigned int d=0; d<Dimension; d++)
{
plhs[d] = mxCreateNumericArray(
Dimension, matlabdims, classID, mxREAL);
fieldoutptrs[d] = static_cast<MatlabPixelType *>(mxGetData(plhs[d]));
}
// read field
VectorPixelType * fieldptr = field->GetBufferPointer();
const VectorPixelType * const buff_end = fieldptr + numPix;
while ( fieldptr != buff_end )
{
for (unsigned int d=0; d<Dimension; d++)
{
*(fieldoutptrs[d])++ = (*fieldptr)[d];
}
++fieldptr;
}
}