[Insight-users] registration .. convergence to fast ...
Mr Gaffe
lagaffe74130 at yahoo.fr
Thu Nov 18 08:06:28 EST 2004
Hello,
The program below is based on registration example and allow an centeredAffineTransform with a iMattesMutualInformation metric...
I test it with BrainT1SliceBorder20.png and BrainProtonDensitySliceR10X13Y17S12.png. The result is not so bad, but not really good ...
I think the convergence is to fast ... I think I had to change some parameters but I don't where ....
Thanks for help
lagaffe
-----------------------------------
Initial Transform Parameters
[1, 0, 0, 1, 110.771, 131.272, -12.3588, -12.3721]
0 -0.494313 [1.03129, 0.0592011, 0.0384303, 1.04259, 110.771, 131.272, -12.3226, -12.3418]
1 -0.506525 [1.01369, 0.0180759, 0.0374976, 1.04872, 110.772, 131.273, -12.3427, -12.3341]
2 -0.497655 [1.01052, 0.00387624, 0.0555589, 1.08858, 110.771, 131.272, -12.3573, -12.3215]
3 -0.476204 [0.985719, -0.0221933, 0.0718157, 1.08991, 110.771, 131.271, -12.3836, -12.3058]
4 -0.46122 [0.952404, -0.0489021, 0.0696406, 1.07258, 110.77, 131.27, -12.4026, -12.3026]
5 -0.46892 [0.951745, -0.0356225, 0.0613028, 1.05532, 110.771, 131.271, -12.3971, -12.3096]
6 -0.476501 [0.942724, -0.0359882, 0.0670168, 1.05927, 110.771, 131.271, -12.4003, -12.3057]
7 -0.476813 [0.934107, -0.0352334, 0.0731064, 1.05942, 110.77, 131.27, -12.4026, -12.2995]
8 -0.481887 [0.9309, -0.0309813, 0.0819638, 1.0591, 110.77, 131.27, -12.4014, -12.2926]
9 -0.485281 [0.927642, -0.0303667, 0.088813, 1.06742, 110.769, 131.269, -12.4017, -12.2872]
10 -0.483528 [0.923046, -0.0309841, 0.0869023, 1.06398, 110.769, 131.27, -12.4023, -12.2885]
11 -0.486905 [0.922546, -0.0292402, 0.0886269, 1.06479, 110.769, 131.269, -12.4015, -12.287]
12 -0.486916 [0.920049, -0.0300743, 0.0896122, 1.06465, 110.769, 131.269, -12.4027, -12.2863]
13 -0.489127 [0.917638, -0.0309204, 0.0903297, 1.06447, 110.769, 131.269, -12.4037, -12.2851]
14 -0.490183 [0.918016, -0.0299934, 0.0909949, 1.06494, 110.769, 131.269, -12.4031, -12.2844]
15 -0.489932 [0.918292, -0.0290254, 0.0916975, 1.06503, 110.769, 131.269, -12.4024, -12.2837]
Result =
Center X = 110.769
Center Y = 131.269
Translation X = -12.4024
Translation Y = -12.2837
Iterations = 17
Metric value = -0.490452
-----------------------
source code if someone want it:
#include "itkImageRegistrationMethod.h"
//#include "itkMeanSquaresImageToImageMetric.h"
#include "itkMattesMutualInformationImageToImageMetric.h"
#include "itkLinearInterpolateImageFunction.h"
#include "itkRegularStepGradientDescentOptimizer.h"
#include "itkImage.h"
#include "itkCenteredTransformInitializer.h"
#include "itkCenteredAffineTransform.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkResampleImageFilter.h"
#include "itkCastImageFilter.h"
#include "itkSquaredDifferenceImageFilter.h"
#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::RegularStepGradientDescentOptimizer 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::endl;
std::cerr << " outputImagefile [differenceOutputfile] [differenceBeforeRegistration] " << std::endl;
std::cerr << " [stepLength] [maxNumberOfIterations] "<< std::endl;
return 1;
}
const unsigned int Dimension = 2;
typedef float PixelType;
typedef itk::Image< PixelType, Dimension > FixedImageType;
typedef itk::Image< PixelType, Dimension > MovingImageType;
typedef itk::CenteredAffineTransform<
double,
Dimension > TransformType;
typedef itk::RegularStepGradientDescentOptimizer OptimizerType;
/*
typedef itk::MeanSquaresImageToImageMetric<
FixedImageType,
MovingImageType > MetricType;
*/
typedef itk::MattesMutualInformationImageToImageMetric<
FixedImageType,
MovingImageType > MetricType;
typedef itk:: LinearInterpolateImageFunction<
MovingImageType,
double > InterpolatorType;
typedef itk::ImageRegistrationMethod<
FixedImageType,
MovingImageType > RegistrationType;
MetricType::Pointer metric = MetricType::New();
OptimizerType::Pointer optimizer = OptimizerType::New();
InterpolatorType::Pointer interpolator = InterpolatorType::New();
RegistrationType::Pointer registration = RegistrationType::New();
registration->SetMetric( metric );
registration->SetOptimizer( optimizer );
registration->SetInterpolator( interpolator );
metric->SetNumberOfHistogramBins( 50 );
metric->SetNumberOfSpatialSamples( 10000 );
TransformType::Pointer transform = TransformType::New();
registration->SetTransform( transform );
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] );
registration->SetFixedImage( fixedImageReader->GetOutput() );
registration->SetMovingImage( movingImageReader->GetOutput() );
fixedImageReader->Update();
registration->SetFixedImageRegion(
fixedImageReader->GetOutput()->GetBufferedRegion() );
typedef itk::CenteredTransformInitializer<
TransformType,
FixedImageType,
MovingImageType > TransformInitializerType;
TransformInitializerType::Pointer initializer = TransformInitializerType::New();
initializer->SetTransform( transform );
initializer->SetFixedImage( fixedImageReader->GetOutput() );
initializer->SetMovingImage( movingImageReader->GetOutput() );
initializer->MomentsOn();
initializer->InitializeTransform();
std::cout << "Initial Transform Parameters " << std::endl;
std::cout << transform->GetParameters() << std::endl;
// -----------------------
registration->SetInitialTransformParameters(
transform->GetParameters() );
double translationScale = 1.0 / 1000.0;
if( argc > 8 )
{
translationScale = atof( argv[8] );
}
typedef OptimizerType::ScalesType OptimizerScalesType;
OptimizerScalesType optimizerScales( transform->GetNumberOfParameters() );
optimizerScales[0] = 0.1;
optimizerScales[1] = 0.1;
optimizerScales[2] = 0.1;
optimizerScales[3] = 0.1;
optimizerScales[4] = translationScale;
optimizerScales[5] = translationScale;
optimizerScales[6] = translationScale;
optimizerScales[7] = translationScale;
optimizer->SetScales( optimizerScales );
double steplength = 0.1;
if( argc > 6 )
{
steplength = atof( argv[6] );
}
unsigned int maxNumberOfIterations = 300;
if( argc > 7 )
{
maxNumberOfIterations = atoi( argv[7] );
}
optimizer->SetMaximumStepLength( steplength );
optimizer->SetMinimumStepLength( 0.001 );
optimizer->SetNumberOfIterations( maxNumberOfIterations );
optimizer->MinimizeOn();
CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
optimizer->AddObserver( itk::IterationEvent(), observer );
try
{
registration->StartRegistration();
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return -1;
}
OptimizerType::ParametersType finalParameters =
registration->GetLastTransformParameters();
const double finalRotationCenterX = finalParameters[4];
const double finalRotationCenterY = finalParameters[5];
const double finalTranslationX = finalParameters[6];
const double finalTranslationY = finalParameters[7];
const unsigned int numberOfIterations = optimizer->GetCurrentIteration();
const double bestValue = optimizer->GetValue();
// Software Guide : EndCodeSnippet
// Print out results
//
std::cout << "Result = " << 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() );
FixedImageType::Pointer fixedImage = fixedImageReader->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( argv[3] );
caster->SetInput( resample->GetOutput() );
writer->SetInput( caster->GetOutput() );
writer->Update();
typedef itk::SquaredDifferenceImageFilter<
FixedImageType,
FixedImageType,
OutputImageType > DifferenceFilterType;
DifferenceFilterType::Pointer difference = DifferenceFilterType::New();
WriterType::Pointer writer2 = WriterType::New();
writer2->SetInput( difference->GetOutput() );
if( argc > 4 )
{
difference->SetInput1( fixedImageReader->GetOutput() );
difference->SetInput2( resample->GetOutput() );
writer2->SetFileName( argv[4] );
writer2->Update();
}
if( argc > 5 )
{
writer2->SetFileName( argv[5] );
difference->SetInput1( fixedImageReader->GetOutput() );
difference->SetInput2( movingImageReader->GetOutput() );
writer2->Update();
}
return 0;
}
---------------------------------
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