[Insight-users] registration .. convergence to fast ...
Luis Ibanez
luis.ibanez at kitware.com
Thu Nov 18 11:27:05 EST 2004
Hi Lagaffe,
1) When you use MutualInformation, you should try to
Maximize it, not to minimize it as you are requesting
in your code:
optimizer->MinimizeOn();
you should rather have
optimizer->MaximizeOn();
2) If the optimizer is terminating too early, that means
that the convergence criteria that you set in the
optimizer are too relaxed. You should therefore explore
different values for :
maximumStepLength
minimumStepLength
3) Note that running a Gradient Descent optimizer in a
cost function as noisy as Mutual Information will
not behave in the monotonical way that you may want.
4) The translation scales are also a critical parameter
of the registration. When you say that the result of
the registration is "not really good"...
did you observe a residual misregistration in the
rotation ?
translation ?
both ?
Regards,
Luis
------------------
Mr Gaffe wrote:
> 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, 0.073106! 4, 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, -12.4! 024, -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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