[Insight-users] Mutual Information rotation & translation and the metric value (with the code)

[Seniha Esen Yuksel]

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");



  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() );




  optimizer->SetLearningRate( 20);
  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] );
  
  //argv[3] 

  caster->SetInput( resample->GetOutput() );
  writer->SetInput( caster->GetOutput()   );
  writer->Update();



  return 0;
}