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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
/**
* Test program for itkMultiStartImageToImageMetricv4RegistrationTest and
* GradientDescentOptimizerv4 classes.
*
* Perform a registration using user-supplied images.
* No numerical verification is performed. Test passes as long
* as no exception occurs.
*/
#include "itkMattesMutualInformationImageToImageMetricv4.h"
#include "itkMeanSquaresImageToImageMetricv4.h"
#include "itkGradientDescentOptimizerv4.h"
#include "itkRegistrationParameterScalesFromPhysicalShift.h"
#include "itkMultiGradientOptimizerv4.h"
#include "itkGaussianSmoothingOnUpdateDisplacementFieldTransform.h"
#include "itkCastImageFilter.h"
#include "itkCommand.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include <iomanip>
int itkMultiGradientImageToImageMetricv4RegistrationTest(int argc, char *argv[])
{
if( argc < 4 )
{
std::cerr << "Missing Parameters " << std::endl;
std::cerr << "Usage: " << argv[0];
std::cerr << " fixedImageFile movingImageFile ";
std::cerr << " outputImageFile ";
std::cerr << " [numberOfIterations initialAffine ] ";
std::cerr << std::endl;
return EXIT_FAILURE;
}
std::cout << argc << std::endl;
unsigned int numberOfIterations = 10;
if( argc >= 5 )
{
numberOfIterations = atoi( argv[4] );
}
std::cout << " iterations "<< numberOfIterations << std::endl;
const unsigned int Dimension = 2;
typedef double PixelType; //I assume png is unsigned short
typedef itk::Image< PixelType, Dimension > FixedImageType;
typedef itk::Image< PixelType, Dimension > MovingImageType;
typedef itk::ImageFileReader< FixedImageType > FixedImageReaderType;
typedef itk::ImageFileReader< MovingImageType > MovingImageReaderType;
FixedImageReaderType::Pointer fixedImageReader = FixedImageReaderType::New();
MovingImageReaderType::Pointer movingImageReader = MovingImageReaderType::New();
fixedImageReader->SetFileName( argv[1] );
movingImageReader->SetFileName( argv[2] );
//get the images
fixedImageReader->Update();
FixedImageType::Pointer fixedImage = fixedImageReader->GetOutput();
movingImageReader->Update();
MovingImageType::Pointer movingImage = movingImageReader->GetOutput();
/** define a resample filter that will ultimately be used to deform the image */
typedef itk::ResampleImageFilter<
MovingImageType,
FixedImageType > ResampleFilterType;
ResampleFilterType::Pointer resample = ResampleFilterType::New();
/** create a composite transform holder for other transforms */
typedef itk::CompositeTransform<double, Dimension> CompositeType;
CompositeType::Pointer compositeTransform = CompositeType::New();
//create an affine transform
typedef itk::AffineTransform<double, Dimension>
AffineTransformType;
AffineTransformType::Pointer affineTransform = AffineTransformType::New();
affineTransform->SetIdentity();
std::cout <<" affineTransform params prior to optimization " << affineTransform->GetParameters() << std::endl;
//identity transform for fixed image
typedef itk::IdentityTransform<double, Dimension> IdentityTransformType;
IdentityTransformType::Pointer identityTransform = IdentityTransformType::New();
identityTransform->SetIdentity();
// The metric
typedef itk::MattesMutualInformationImageToImageMetricv4 < FixedImageType, MovingImageType > MetricType;
typedef itk::MeanSquaresImageToImageMetricv4 < FixedImageType, MovingImageType > MetricType2;
typedef MetricType::FixedSampledPointSetType PointSetType;
MetricType::Pointer metric = MetricType::New();
metric->SetNumberOfHistogramBins(20);
MetricType2::Pointer metric2 = MetricType2::New();
if( 0 )
{
std::cout << "Dense sampling." << std::endl;
metric->SetUseFixedSampledPointSet( false );
}
else
{
typedef PointSetType::PointType PointType;
PointSetType::Pointer pset(PointSetType::New());
unsigned long ind=0,ct=0;
itk::ImageRegionIteratorWithIndex<FixedImageType> It(fixedImage, fixedImage->GetLargestPossibleRegion() );
for( It.GoToBegin(); !It.IsAtEnd(); ++It )
{
// take every N^th point
if ( ct % 20 == 0 )
{
PointType pt;
fixedImage->TransformIndexToPhysicalPoint( It.GetIndex(), pt);
pset->SetPoint(ind, pt);
ind++;
}
ct++;
}
metric->SetFixedSampledPointSet( pset );
metric->SetUseFixedSampledPointSet( true );
metric2->SetFixedSampledPointSet( pset );
metric2->SetUseFixedSampledPointSet( true );
std::cout << "Testing metric with point set..." << std::endl;
}
metric->SetFixedImage( fixedImage );
metric->SetMovingImage( movingImage );
metric->SetFixedTransform( identityTransform );
metric->SetMovingTransform( affineTransform );
metric->SetUseMovingImageGradientFilter( false );
metric->SetUseFixedImageGradientFilter( false );
metric->Initialize();
metric2->SetFixedImage( fixedImage );
metric2->SetMovingImage( movingImage );
metric2->SetFixedTransform( identityTransform );
metric2->SetMovingTransform( affineTransform );
metric2->SetUseMovingImageGradientFilter( false );
metric2->SetUseFixedImageGradientFilter( false );
metric2->Initialize();
std::cout << "First do an affine registration " << std::endl;
typedef itk::RegistrationParameterScalesFromPhysicalShift< MetricType > RegistrationParameterScalesFromShiftType;
RegistrationParameterScalesFromShiftType::Pointer shiftScaleEstimator = RegistrationParameterScalesFromShiftType::New();
RegistrationParameterScalesFromShiftType::ScalesType scales(affineTransform->GetNumberOfParameters());
shiftScaleEstimator->SetMetric(metric);
shiftScaleEstimator->EstimateScales(scales);
typedef itk::GradientDescentOptimizerv4 OptimizerType;
OptimizerType::Pointer optimizer = OptimizerType::New();
optimizer->SetMetric( metric );
optimizer->SetScales(scales);
/** Set just 1 iteration for the sub-optimizer */
optimizer->SetNumberOfIterations( 1 );
optimizer->SetScalesEstimator( shiftScaleEstimator );
optimizer->SetMaximumStepSizeInPhysicalUnits( 0.5 );
std::cout << "now declare optimizer2 " << std::endl;
typedef itk::RegistrationParameterScalesFromPhysicalShift< MetricType2 > RegistrationParameterScalesFromShiftType2;
RegistrationParameterScalesFromShiftType2::Pointer shiftScaleEstimator2 = RegistrationParameterScalesFromShiftType2::New();
shiftScaleEstimator2->SetMetric(metric2);
shiftScaleEstimator2->EstimateScales(scales);
OptimizerType::Pointer optimizer2 = OptimizerType::New();
optimizer2->SetMetric( metric2 );
optimizer2->SetScales(scales);
/** Set just 1 iteration for the sub-optimizer */
optimizer2->SetNumberOfIterations( 1 );
optimizer2->SetScalesEstimator( shiftScaleEstimator2 );
optimizer2->SetMaximumStepSizeInPhysicalUnits( 0.5 );
std::cout << "now declare optimizer to combine the 2 sub-optimizers " << std::endl;
typedef itk::MultiGradientOptimizerv4 MOptimizerType;
MOptimizerType::Pointer MOptimizer = MOptimizerType::New();
MOptimizer->GetOptimizersList().push_back(optimizer);
MOptimizer->GetOptimizersList().push_back(optimizer2);
std::cout << "set the # of iterations " << std::endl;
MOptimizer->SetNumberOfIterations( numberOfIterations );
std::cout << "begin optimization " << std::endl;
MOptimizer->StartOptimization();
//warp the image with the displacement field
resample->SetTransform( affineTransform );
resample->SetInput( movingImageReader->GetOutput() );
resample->SetSize( fixedImage->GetLargestPossibleRegion().GetSize() );
resample->SetOutputOrigin( fixedImage->GetOrigin() );
resample->SetOutputSpacing( fixedImage->GetSpacing() );
resample->SetOutputDirection( fixedImage->GetDirection() );
resample->SetDefaultPixelValue( 0 );
resample->Update();
std::cout << "GetNumberOfThreadsUsed: " << metric->GetNumberOfThreadsUsed() << std::endl;
//write the warped image into a file
typedef double OutputPixelType;
typedef itk::Image< OutputPixelType, Dimension > OutputImageType;
typedef itk::CastImageFilter<
MovingImageType,
OutputImageType > CastFilterType;
typedef itk::ImageFileWriter< OutputImageType > WriterType;
WriterType::Pointer writer = WriterType::New();
CastFilterType::Pointer caster = CastFilterType::New();
writer->SetFileName( argv[3] );
caster->SetInput( resample->GetOutput() );
writer->SetInput( caster->GetOutput() );
writer->Update();
std::cout << "After optimization affine params are: " << affineTransform->GetParameters() << std::endl;
std::cout << "Test PASSED." << std::endl;
return EXIT_SUCCESS;
}
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