double antsImageMIHelper(
typename itk::Image< float , Dimension >::Pointer image1,
typename itk::Image< float , Dimension >::Pointer image2 )
{
typedef itk::Image< float , Dimension > ImageType;
if( image1.IsNotNull() & image2.IsNotNull() )
{
double mi = 1;
typedef itk::MattesMutualInformationImageToImageMetricv4
<ImageType, ImageType, ImageType> MetricType;
unsigned int bins = 32;
typename MetricType::Pointer metric = MetricType::New();
metric->SetFixedImage( image1 );
metric->SetMovingImage( image2 );
metric->SetNumberOfHistogramBins( bins );
metric->Initialize();
mi = metric->GetValue();
return mi;
}
else
{
return 1;
}
}
template<class FixedImageType,class MovingImageType,class TransformType> void RegisterPair(const typename FixedImageType::Pointer & fixedImage, const typename MovingImageType::Pointer & movingImage, typename TransformType::Pointer & transform ){
typedef itk::LogImageAdaptor<FixedImageType,float> LogFixedImageType;
typedef itk::CenteredTransformInitializer< TransformType,LogFixedImageType,MovingImageType> TransformInitializerType;
typename TransformInitializerType::Pointer initializer = TransformInitializerType::New();
typename LogFixedImageType::Pointer logAdaptor=LogFixedImageType::New();
logAdaptor->SetImage(fixedImage);
initializer->SetTransform( transform );
initializer->SetFixedImage( logAdaptor );
initializer->SetMovingImage( movingImage);
initializer->MomentsOn();
initializer->InitializeTransform();
// Optimizer Type
typedef itk::VersorRigid3DTransformOptimizer OptimizerType;
//typedef itk::ConjugateGradientOptimizer OptimizerType;
// Metric Type
typedef
//itk::NormalizedMutualInformationHistogramImageToImageMetric< FixedImageType, MovingImageType >
//itk::MutualInformationImageToImageMetric<FixedImageType,MovingImageType >
//itk::GradientDifferenceImageToImageMetric<FixedImageType,MovingImageType>
itk::NormalizedCorrelationImageToImageMetric< FixedImageType, MovingImageType >
// itk::KullbackLeiblerCompareHistogramImageToImageMetric< FixedImageType, MovingImageType >
//itk::MattesMutualInformationImageToImageMetric<FixedImageType,MovingImageType>
//itk::MutualInformationHistogramImageToImageMetric<FixedImageType,MovingImageType>
//itk::MeanSquaresImageToImageMetric< FixedImageType, MovingImageType >
MetricType;
// Interpolation technique
typedef itk:: LinearInterpolateImageFunction<
MovingImageType,
double > InterpolatorType;
// Registration Method
typedef itk::ImageRegistrationMethod<
FixedImageType,
MovingImageType > RegistrationType;
typename MetricType::Pointer metric = MetricType::New();
typename OptimizerType::Pointer optimizer = OptimizerType::New();
typename InterpolatorType::Pointer interpolator = InterpolatorType::New();
typename RegistrationType::Pointer registration = RegistrationType::New();
/******************************************************************
* Set up the optimizer.
******************************************************************/
typedef typename TransformType::VersorType VersorType;
typedef typename VersorType::VectorType VectorType;
VersorType rotation;
VectorType axis;
axis[0] = 0.0;
axis[1] = 0.0;
axis[2] = 1.0;
const double angle = 0;
rotation.Set( axis, angle );
transform->SetRotation( rotation );
registration->SetInitialTransformParameters( transform->GetParameters() );
// Software Guide : EndCodeSnippet
typedef OptimizerType::ScalesType OptimizerScalesType;
OptimizerScalesType optimizerScales( transform->GetNumberOfParameters() );
const double translationScale = 1.0 / 1000.0;
optimizerScales[0] = 1.0;
optimizerScales[1] = 1.0;
optimizerScales[2] = 1.0;
optimizerScales[3] = translationScale;
optimizerScales[4] = translationScale;
optimizerScales[5] = translationScale;
optimizer->SetScales( optimizerScales );
//optimizer->SetMaximumStepLength( 0.1 );
optimizer->SetMaximumStepLength( 1);
optimizer->SetMinimumStepLength( 0.000000001 );
optimizer->SetNumberOfIterations( 10 );
optimizer->SetMinimize(true);
/******************************************************************
* Set up the metric.
******************************************************************/
//metric->SetMovingImageStandardDeviation( 1.0 );
//metric->SetFixedImageStandardDeviation( 1.0 );
//metric->SetNumberOfSpatialSamples( 50000000 );
metric->SetUseAllPixels(true);
//metric->SetFixedImageRegion( fixedImage->GetBufferedRegion() );
/******************************************************************
* Set up the registrator.
******************************************************************/
// connect up the components
registration->SetMetric( metric );
registration->SetOptimizer( optimizer );
registration->SetTransform( transform );
registration->SetFixedImage( fixedImage );
registration->SetMovingImage( movingImage );
registration->SetInterpolator( interpolator );
// transform->SetIdentity();
// // set initial parameters to identity
// typename RegistrationType::ParametersType initialParameters(
// transform->GetNumberOfParameters() );
//
// initialParameters.Fill( 0.0 );
// //initialParameters[3] = 1.0;
CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
optimizer->AddObserver( itk::IterationEvent(), observer );
try
{
registration->Update();
std::cout << "Optimizer stop condition: "
<< registration->GetOptimizer()->GetStopConditionDescription()
<< std::endl;
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
//return EXIT_FAILURE;
}
OptimizerType::ParametersType finalParameters =
registration->GetLastTransformParameters();
const double versorX = finalParameters[0];
const double versorY = finalParameters[1];
const double versorZ = finalParameters[2];
const double finalTranslationX = finalParameters[3];
const double finalTranslationY = finalParameters[4];
const double finalTranslationZ = finalParameters[5];
const unsigned int numberOfIterations = optimizer->GetCurrentIteration();
const double bestValue = optimizer->GetValue();
// Print out results
//
std::cout << std::endl << std::endl;
std::cout << "Result = " << std::endl;
std::cout << " versor X = " << versorX << std::endl;
std::cout << " versor Y = " << versorY << std::endl;
std::cout << " versor Z = " << versorZ << std::endl;
std::cout << " Translation X = " << finalTranslationX << std::endl;
std::cout << " Translation Y = " << finalTranslationY << std::endl;
std::cout << " Translation Z = " << finalTranslationZ << std::endl;
std::cout << " Iterations = " << numberOfIterations << std::endl;
std::cout << " Metric value = " << bestValue << std::endl;
}
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;
}
}
}
SEXP invariantSimilarityHelper(
typename itk::Image< float , ImageDimension >::Pointer image1,
typename itk::Image< float , ImageDimension >::Pointer image2,
SEXP r_thetas, SEXP r_lsits, SEXP r_WM, SEXP r_scale,
SEXP r_doreflection, SEXP r_txfn )
{
unsigned int mibins = 20;
unsigned int localSearchIterations =
Rcpp::as< unsigned int >( r_lsits ) ;
std::string whichMetric = Rcpp::as< std::string >( r_WM );
std::string txfn = Rcpp::as< std::string >( r_txfn );
bool useprincaxis = true;
typedef typename itk::ImageMaskSpatialObject<ImageDimension>::ImageType
maskimagetype;
typename maskimagetype::Pointer mask = ITK_NULLPTR;
Rcpp::NumericVector thetas( r_thetas );
Rcpp::NumericVector vector_r( r_thetas ) ;
Rcpp::IntegerVector dims( 1 );
Rcpp::IntegerVector doReflection( r_doreflection );
unsigned int vecsize = thetas.size();
dims[0]=0;
typedef float PixelType;
typedef double RealType;
RealType bestscale = Rcpp::as< RealType >( r_scale ) ;
typedef itk::Image< PixelType , ImageDimension > ImageType;
if( image1.IsNotNull() & image2.IsNotNull() )
{
typedef typename itk::ImageMomentsCalculator<ImageType> ImageCalculatorType;
typedef itk::AffineTransform<RealType, ImageDimension> AffineType0;
typedef itk::AffineTransform<RealType, ImageDimension> AffineType;
typedef typename ImageCalculatorType::MatrixType MatrixType;
typedef itk::Vector<float, ImageDimension> VectorType;
VectorType ccg1;
VectorType cpm1;
MatrixType cpa1;
VectorType ccg2;
VectorType cpm2;
MatrixType cpa2;
typename ImageCalculatorType::Pointer calculator1 =
ImageCalculatorType::New();
typename ImageCalculatorType::Pointer calculator2 =
ImageCalculatorType::New();
calculator1->SetImage( image1 );
calculator2->SetImage( image2 );
typename ImageCalculatorType::VectorType fixed_center;
fixed_center.Fill(0);
typename ImageCalculatorType::VectorType moving_center;
moving_center.Fill(0);
try
{
calculator1->Compute();
fixed_center = calculator1->GetCenterOfGravity();
ccg1 = calculator1->GetCenterOfGravity();
cpm1 = calculator1->GetPrincipalMoments();
cpa1 = calculator1->GetPrincipalAxes();
try
{
calculator2->Compute();
moving_center = calculator2->GetCenterOfGravity();
ccg2 = calculator2->GetCenterOfGravity();
cpm2 = calculator2->GetPrincipalMoments();
cpa2 = calculator2->GetPrincipalAxes();
}
catch( ... )
{
fixed_center.Fill(0);
}
}
catch( ... )
{
// Rcpp::Rcerr << " zero image1 error ";
}
if ( vnl_math_abs( bestscale - 1.0 ) < 1.e-6 )
{
RealType volelt1 = 1;
RealType volelt2 = 1;
for ( unsigned int d=0; d<ImageDimension; d++)
{
volelt1 *= image1->GetSpacing()[d];
volelt2 *= image2->GetSpacing()[d];
}
bestscale =
( calculator2->GetTotalMass() * volelt2 )/
( calculator1->GetTotalMass() * volelt1 );
RealType powlev = 1.0 / static_cast<RealType>(ImageDimension);
bestscale = vcl_pow( bestscale , powlev );
}
unsigned int eigind1 = 1;
unsigned int eigind2 = 1;
if( ImageDimension == 3 )
{
eigind1 = 2;
}
typedef vnl_vector<RealType> EVectorType;
typedef vnl_matrix<RealType> EMatrixType;
EVectorType evec1_2ndary = cpa1.GetVnlMatrix().get_row( eigind2 );
EVectorType evec1_primary = cpa1.GetVnlMatrix().get_row( eigind1 );
EVectorType evec2_2ndary = cpa2.GetVnlMatrix().get_row( eigind2 );
EVectorType evec2_primary = cpa2.GetVnlMatrix().get_row( eigind1 );
/** Solve Wahba's problem http://en.wikipedia.org/wiki/Wahba%27s_problem */
EMatrixType B = outer_product( evec2_primary, evec1_primary );
if( ImageDimension == 3 )
{
B = outer_product( evec2_2ndary, evec1_2ndary )
+ outer_product( evec2_primary, evec1_primary );
}
vnl_svd<RealType> wahba( B );
vnl_matrix<RealType> A_solution = wahba.V() * wahba.U().transpose();
A_solution = vnl_inverse( A_solution );
RealType det = vnl_determinant( A_solution );
if( ( det < 0 ) )
{
vnl_matrix<RealType> id( A_solution );
id.set_identity();
for( unsigned int i = 0; i < ImageDimension; i++ )
{
if( A_solution( i, i ) < 0 )
{
id( i, i ) = -1.0;
}
}
A_solution = A_solution * id.transpose();
}
if ( doReflection[0] == 1 || doReflection[0] == 3 )
{
vnl_matrix<RealType> id( A_solution );
id.set_identity();
id = id - 2.0 * outer_product( evec2_primary , evec2_primary );
A_solution = A_solution * id;
}
if ( doReflection[0] > 1 )
{
vnl_matrix<RealType> id( A_solution );
id.set_identity();
id = id - 2.0 * outer_product( evec1_primary , evec1_primary );
A_solution = A_solution * id;
}
typename AffineType::Pointer affine1 = AffineType::New();
typename AffineType::OffsetType trans = affine1->GetOffset();
itk::Point<RealType, ImageDimension> trans2;
for( unsigned int i = 0; i < ImageDimension; i++ )
{
trans[i] = moving_center[i] - fixed_center[i];
trans2[i] = fixed_center[i] * ( 1 );
}
affine1->SetIdentity();
affine1->SetOffset( trans );
if( useprincaxis )
{
affine1->SetMatrix( A_solution );
}
affine1->SetCenter( trans2 );
if( ImageDimension > 3 )
{
return EXIT_SUCCESS;
}
vnl_vector<RealType> evec_tert;
if( ImageDimension == 3 )
{ // try to rotate around tertiary and secondary axis
evec_tert = vnl_cross_3d( evec1_primary, evec1_2ndary );
}
if( ImageDimension == 2 )
{ // try to rotate around tertiary and secondary axis
evec_tert = evec1_2ndary;
evec1_2ndary = evec1_primary;
}
itk::Vector<RealType, ImageDimension> axis2;
itk::Vector<RealType, ImageDimension> axis1;
for( unsigned int d = 0; d < ImageDimension; d++ )
{
axis1[d] = evec_tert[d];
axis2[d] = evec1_2ndary[d];
}
typename AffineType::Pointer simmer = AffineType::New();
simmer->SetIdentity();
simmer->SetCenter( trans2 );
simmer->SetOffset( trans );
typename AffineType0::Pointer affinesearch = AffineType0::New();
affinesearch->SetIdentity();
affinesearch->SetCenter( trans2 );
typedef itk::MultiStartOptimizerv4 OptimizerType;
typename OptimizerType::MetricValuesListType metricvalues;
typename OptimizerType::Pointer mstartOptimizer = OptimizerType::New();
typedef itk::CorrelationImageToImageMetricv4
<ImageType, ImageType, ImageType> GCMetricType;
typedef itk::MattesMutualInformationImageToImageMetricv4
<ImageType, ImageType, ImageType> MetricType;
typename MetricType::ParametersType newparams( affine1->GetParameters() );
typename GCMetricType::Pointer gcmetric = GCMetricType::New();
gcmetric->SetFixedImage( image1 );
gcmetric->SetVirtualDomainFromImage( image1 );
gcmetric->SetMovingImage( image2 );
gcmetric->SetMovingTransform( simmer );
gcmetric->SetParameters( newparams );
typename MetricType::Pointer mimetric = MetricType::New();
mimetric->SetNumberOfHistogramBins( mibins );
mimetric->SetFixedImage( image1 );
mimetric->SetMovingImage( image2 );
mimetric->SetMovingTransform( simmer );
mimetric->SetParameters( newparams );
if( mask.IsNotNull() )
{
typename itk::ImageMaskSpatialObject<ImageDimension>::Pointer so =
itk::ImageMaskSpatialObject<ImageDimension>::New();
so->SetImage( const_cast<maskimagetype *>( mask.GetPointer() ) );
mimetric->SetFixedImageMask( so );
gcmetric->SetFixedImageMask( so );
}
typedef itk::ConjugateGradientLineSearchOptimizerv4 LocalOptimizerType;
typename LocalOptimizerType::Pointer localoptimizer =
LocalOptimizerType::New();
RealType localoptimizerlearningrate = 0.1;
localoptimizer->SetLearningRate( localoptimizerlearningrate );
localoptimizer->SetMaximumStepSizeInPhysicalUnits(
localoptimizerlearningrate );
localoptimizer->SetNumberOfIterations( localSearchIterations );
localoptimizer->SetLowerLimit( 0 );
localoptimizer->SetUpperLimit( 2 );
localoptimizer->SetEpsilon( 0.1 );
localoptimizer->SetMaximumLineSearchIterations( 50 );
localoptimizer->SetDoEstimateLearningRateOnce( true );
localoptimizer->SetMinimumConvergenceValue( 1.e-6 );
localoptimizer->SetConvergenceWindowSize( 5 );
if( true )
{
typedef typename MetricType::FixedSampledPointSetType PointSetType;
typedef typename PointSetType::PointType PointType;
typename PointSetType::Pointer pset(PointSetType::New());
unsigned int ind=0;
unsigned int ct=0;
itk::ImageRegionIteratorWithIndex<ImageType> It(image1,
image1->GetLargestPossibleRegion() );
for( It.GoToBegin(); !It.IsAtEnd(); ++It )
{
// take every N^th point
if ( ct % 10 == 0 )
{
PointType pt;
image1->TransformIndexToPhysicalPoint( It.GetIndex(), pt);
pset->SetPoint(ind, pt);
ind++;
}
ct++;
}
mimetric->SetFixedSampledPointSet( pset );
mimetric->SetUseFixedSampledPointSet( true );
gcmetric->SetFixedSampledPointSet( pset );
gcmetric->SetUseFixedSampledPointSet( true );
}
if ( whichMetric.compare("MI") == 0 ) {
mimetric->Initialize();
typedef itk::RegistrationParameterScalesFromPhysicalShift<MetricType>
RegistrationParameterScalesFromPhysicalShiftType;
typename RegistrationParameterScalesFromPhysicalShiftType::Pointer
shiftScaleEstimator =
RegistrationParameterScalesFromPhysicalShiftType::New();
shiftScaleEstimator->SetMetric( mimetric );
shiftScaleEstimator->SetTransformForward( true );
typename RegistrationParameterScalesFromPhysicalShiftType::ScalesType
movingScales( simmer->GetNumberOfParameters() );
shiftScaleEstimator->EstimateScales( movingScales );
mstartOptimizer->SetScales( movingScales );
mstartOptimizer->SetMetric( mimetric );
localoptimizer->SetMetric( mimetric );
localoptimizer->SetScales( movingScales );
}
if ( whichMetric.compare("MI") != 0 ) {
gcmetric->Initialize();
typedef itk::RegistrationParameterScalesFromPhysicalShift<GCMetricType>
RegistrationParameterScalesFromPhysicalShiftType;
typename RegistrationParameterScalesFromPhysicalShiftType::Pointer
shiftScaleEstimator =
RegistrationParameterScalesFromPhysicalShiftType::New();
shiftScaleEstimator->SetMetric( gcmetric );
shiftScaleEstimator->SetTransformForward( true );
typename RegistrationParameterScalesFromPhysicalShiftType::ScalesType
movingScales( simmer->GetNumberOfParameters() );
shiftScaleEstimator->EstimateScales( movingScales );
mstartOptimizer->SetScales( movingScales );
mstartOptimizer->SetMetric( gcmetric );
localoptimizer->SetMetric( gcmetric );
localoptimizer->SetScales( movingScales );
}
typename OptimizerType::ParametersListType parametersList =
mstartOptimizer->GetParametersList();
affinesearch->SetIdentity();
affinesearch->SetCenter( trans2 );
affinesearch->SetOffset( trans );
for ( unsigned int i = 0; i < vecsize; i++ )
{
RealType ang1 = thetas[i];
RealType ang2 = 0; // FIXME should be psi
vector_r[ i ]=0;
if( ImageDimension == 3 )
{
for ( unsigned int jj = 0; jj < vecsize; jj++ )
{
ang2=thetas[jj];
affinesearch->SetIdentity();
affinesearch->SetCenter( trans2 );
affinesearch->SetOffset( trans );
if( useprincaxis )
{
affinesearch->SetMatrix( A_solution );
}
affinesearch->Rotate3D(axis1, ang1, 1);
affinesearch->Rotate3D(axis2, ang2, 1);
affinesearch->Scale( bestscale );
simmer->SetMatrix( affinesearch->GetMatrix() );
parametersList.push_back( simmer->GetParameters() );
}
}
if( ImageDimension == 2 )
{
affinesearch->SetIdentity();
affinesearch->SetCenter( trans2 );
affinesearch->SetOffset( trans );
if( useprincaxis )
{
affinesearch->SetMatrix( A_solution );
}
affinesearch->Rotate2D( ang1, 1);
affinesearch->Scale( bestscale );
simmer->SetMatrix( affinesearch->GetMatrix() );
typename AffineType::ParametersType pp =
simmer->GetParameters();
//pp[1]=ang1;
//pp[0]=bestscale;
parametersList.push_back( simmer->GetParameters() );
}
}
mstartOptimizer->SetParametersList( parametersList );
if( localSearchIterations > 0 )
{
mstartOptimizer->SetLocalOptimizer( localoptimizer );
}
mstartOptimizer->StartOptimization();
typename AffineType::Pointer bestaffine = AffineType::New();
bestaffine->SetCenter( trans2 );
bestaffine->SetParameters( mstartOptimizer->GetBestParameters() );
if ( txfn.length() > 3 )
{
typename AffineType::Pointer bestaffine = AffineType::New();
bestaffine->SetCenter( trans2 );
bestaffine->SetParameters( mstartOptimizer->GetBestParameters() );
typedef itk::TransformFileWriter TransformWriterType;
typename TransformWriterType::Pointer transformWriter =
TransformWriterType::New();
transformWriter->SetInput( bestaffine );
transformWriter->SetFileName( txfn.c_str() );
transformWriter->Update();
}
metricvalues = mstartOptimizer->GetMetricValuesList();
for ( unsigned int k = 0; k < metricvalues.size(); k++ )
{
vector_r[k] = metricvalues[k];
}
dims[0] = vecsize;
vector_r.attr( "dim" ) = vecsize;
return Rcpp::wrap( vector_r );
}
else
{
return Rcpp::wrap( vector_r );
}
}
