[Insight-users] Mutual Information rotation & translation and the
metric value (with the code)
Seniha Esen Yuksel
eseny99 at yahoo.com
Tue Jul 26 12:59:49 EDT 2005
Skipped content of type multipart/alternative-------------- next part --------------
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: ImageRegistration2.cxx,v $
Language: C++
Date: $Date: 2004/12/28 14:42:49 $
Version: $Revision: 1.33 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm 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 "itkImageRegistrationMethod.h"
#include "itkCenteredRigid2DTransform.h"
#include "itkMutualInformationImageToImageMetric.h"
#include "itkLinearInterpolateImageFunction.h"
#include "itkGradientDescentOptimizer.h"
#include "itkImage.h"
#include "itkNormalizeImageFilter.h"
#include "itkDiscreteGaussianImageFilter.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkResampleImageFilter.h"
#include "itkCastImageFilter.h"
// The following section of code implements a Command observer
// that will monitor the evolution of the registration process.
//
#include "itkCommand.h"
class CommandIterationUpdate : public itk::Command
{
public:
typedef CommandIterationUpdate Self;
typedef itk::Command Superclass;
typedef itk::SmartPointer<Self> Pointer;
itkNewMacro( Self );
protected:
CommandIterationUpdate() {};
public:
typedef itk::GradientDescentOptimizer OptimizerType;
typedef const OptimizerType * OptimizerPointer;
void Execute(itk::Object *caller, const itk::EventObject & event)
{
Execute( (const itk::Object *)caller, event);
}
void Execute(const itk::Object * object, const itk::EventObject & event)
{
OptimizerPointer optimizer =
dynamic_cast< OptimizerPointer >( object );
if( typeid( event ) != typeid( itk::IterationEvent ) )
{
return;
}
std::cout << optimizer->GetCurrentIteration() << " ";
std::cout << optimizer->GetValue() << " ";
std::cout << optimizer->GetCurrentPosition() << std::endl;
}
};
int main( 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::endl;
return 1;
}
*/
const unsigned int Dimension = 2;
typedef unsigned short PixelType;
typedef itk::Image< PixelType, Dimension > FixedImageType;
typedef itk::Image< PixelType, Dimension > MovingImageType;
typedef float InternalPixelType;
typedef itk::Image< InternalPixelType, Dimension > InternalImageType;
typedef itk::CenteredRigid2DTransform< double > TransformType;
typedef itk::GradientDescentOptimizer OptimizerType;
typedef itk::LinearInterpolateImageFunction<
InternalImageType,
double > InterpolatorType;
typedef itk::ImageRegistrationMethod<
InternalImageType,
InternalImageType > RegistrationType;
typedef itk::MutualInformationImageToImageMetric<
InternalImageType,
InternalImageType > MetricType;
TransformType::Pointer transform = TransformType::New();
OptimizerType::Pointer optimizer = OptimizerType::New();
InterpolatorType::Pointer interpolator = InterpolatorType::New();
RegistrationType::Pointer registration = RegistrationType::New();
registration->SetOptimizer( optimizer );
registration->SetTransform( transform );
registration->SetInterpolator( interpolator );
MetricType::Pointer metric = MetricType::New();
registration->SetMetric( metric );
metric->SetFixedImageStandardDeviation( 0.4 );
metric->SetMovingImageStandardDeviation( 0.4 );
metric->SetNumberOfSpatialSamples( 50 );
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] );
//fixedImageReader->SetFileName( "original.png" );
//movingImageReader->SetFileName( "rotate.png");
//fixedImageReader->SetFileName( "kidney_original_noise_phantom.bmp" );
// movingImageReader->SetFileName( "kidney_rotated_noise_phantom.bmp");
fixedImageReader->SetFileName( "BrainProtonDensitySliceBorder20.png" );
movingImageReader->SetFileName( "BrainProtonDensitySliceR10X13Y17.png" );
typedef itk::NormalizeImageFilter<
FixedImageType,
InternalImageType
> FixedNormalizeFilterType;
typedef itk::NormalizeImageFilter<
MovingImageType,
InternalImageType
> MovingNormalizeFilterType;
FixedNormalizeFilterType::Pointer fixedNormalizer =
FixedNormalizeFilterType::New();
MovingNormalizeFilterType::Pointer movingNormalizer =
MovingNormalizeFilterType::New();
typedef itk::DiscreteGaussianImageFilter<
InternalImageType,
InternalImageType
> GaussianFilterType;
GaussianFilterType::Pointer fixedSmoother = GaussianFilterType::New();
GaussianFilterType::Pointer movingSmoother = GaussianFilterType::New();
fixedSmoother->SetVariance( 2.0 );
movingSmoother->SetVariance( 2.0 );
fixedNormalizer->SetInput( fixedImageReader->GetOutput() );
movingNormalizer->SetInput( movingImageReader->GetOutput() );
fixedSmoother->SetInput( fixedNormalizer->GetOutput() );
movingSmoother->SetInput( movingNormalizer->GetOutput() );
// fixedSmoother->Update();
// movingSmoother->Update();
registration->SetFixedImage( fixedSmoother->GetOutput() );
registration->SetMovingImage( movingSmoother->GetOutput() );
fixedNormalizer->Update();
//movingNormalizer->Update();
registration->SetFixedImageRegion(
fixedNormalizer->GetOutput()->GetBufferedRegion() );
fixedImageReader->Update();
movingImageReader->Update();
FixedImageType::Pointer fixedImage = fixedImageReader->GetOutput();
const FixedImageType::SpacingType&
fixedSpacing = fixedImage->GetSpacing();
const FixedImageType::PointType&
fixedOrigin = fixedImage->GetOrigin();
FixedImageType::SizeType fixedSize =
fixedImage->GetLargestPossibleRegion().GetSize();
TransformType::InputPointType centerFixed;
centerFixed[0] = fixedOrigin[0] + fixedSpacing[0] * fixedSize[0] / 2.0;
centerFixed[1] = fixedOrigin[1] + fixedSpacing[1] * fixedSize[1] / 2.0;
MovingImageType::Pointer movingImage = movingImageReader->GetOutput();
const MovingImageType::SpacingType&
movingSpacing = movingImage->GetSpacing();
const MovingImageType::PointType&
movingOrigin = movingImage->GetOrigin();
MovingImageType::SizeType movingSize =
movingImage->GetLargestPossibleRegion().GetSize();
TransformType::InputPointType centerMoving;
centerMoving[0] = movingOrigin[0] + movingSpacing[0] * movingSize[0] / 2.0;
centerMoving[1] = movingOrigin[1] + movingSpacing[1] * movingSize[1] / 2.0;
transform->SetCenter( centerFixed );
transform->SetTranslation( centerMoving - centerFixed );
transform->SetAngle( 0.0 );
// Now we pass the current transform's parameters as the initial
// parameters to be used when the registration process starts.
registration->SetInitialTransformParameters( transform->GetParameters() );
typedef OptimizerType::ScalesType OptimizerScalesType;
OptimizerScalesType optimizerScales( transform->GetNumberOfParameters() );
// const double translationScale = 1.0 / 1000.0;
const double translationScale = 1.0 /3390.0;
// const double translationScale1 = 1.0 /110.0;
// const double translationScale2 = 1.0 /128.0;
optimizerScales[0] = 1.0;
optimizerScales[1] = translationScale;
optimizerScales[2] = translationScale;
optimizerScales[3] = translationScale;
optimizerScales[4] = translationScale;
optimizer->SetScales( optimizerScales );
optimizer->SetLearningRate( 10);
optimizer->SetNumberOfIterations( 500 );
optimizer->MaximizeOn();
// Create the Command observer and register it with the optimizer.
//
CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
optimizer->AddObserver( itk::IterationEvent(), observer );
try
{
registration->StartRegistration();
}
catch( itk::ExceptionObject & err )
{
std::cout << "ExceptionObject caught !" << std::endl;
std::cout << err << std::endl;
return -1;
}
OptimizerType::ParametersType finalParameters =
registration->GetLastTransformParameters();
const double finalAngle = finalParameters[0];
const double finalRotationCenterX = finalParameters[1];
const double finalRotationCenterY = finalParameters[2];
const double finalTranslationX = finalParameters[3];
const double finalTranslationY = finalParameters[4];
unsigned int numberOfIterations = optimizer->GetCurrentIteration();
double bestValue = optimizer->GetValue();
const double finalAngleInDegrees = finalAngle * 45.0 / atan(1.0);
std::cout << "Result = " << std::endl;
std::cout << " Angle (radians) = " << finalAngle << std::endl;
std::cout << " Angle (degrees) = " << finalAngleInDegrees << std::endl;
std::cout << " Center X = " << finalRotationCenterX << std::endl;
std::cout << " Center Y = " << finalRotationCenterY << std::endl;
std::cout << " Translation X = " << finalTranslationX << std::endl;
std::cout << " Translation Y = " << finalTranslationY << std::endl;
std::cout << " Iterations = " << numberOfIterations << std::endl;
std::cout << " Metric value = " << bestValue << std::endl;
typedef itk::ResampleImageFilter<
MovingImageType,
FixedImageType > ResampleFilterType;
TransformType::Pointer finalTransform = TransformType::New();
finalTransform->SetParameters( finalParameters );
ResampleFilterType::Pointer resample = ResampleFilterType::New();
resample->SetTransform( finalTransform );
resample->SetInput( movingImageReader->GetOutput() );
resample->SetSize( fixedImage->GetLargestPossibleRegion().GetSize() );
resample->SetOutputOrigin( fixedImage->GetOrigin() );
resample->SetOutputSpacing( fixedImage->GetSpacing() );
resample->SetDefaultPixelValue( 100 );
typedef unsigned char OutputPixelType;
typedef itk::Image< OutputPixelType, Dimension > OutputImageType;
typedef itk::CastImageFilter<
FixedImageType,
OutputImageType > CastFilterType;
typedef itk::ImageFileWriter< OutputImageType > WriterType;
WriterType::Pointer writer = WriterType::New();
CastFilterType::Pointer caster = CastFilterType::New();
writer->SetFileName( "result.png" );
// writer->SetFileName( argv[3] );
caster->SetInput( resample->GetOutput() );
writer->SetInput( caster->GetOutput() );
writer->Update();
return 0;
}
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