Examples/RegistrationITKv4/DeformableRegistration7.cxx

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 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
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// Software Guide : BeginLatex
//
// This example illustrates the use of the \doxygen{BSplineTransform}
// class for performing registration of two $3D$ images. The example code is
// for the most part identical to the code presented in
// Section~\ref{sec:BSplinesMultiGridImageRegistration}. The major difference is
// that in this example we set the image dimension to 3 and replace the
// \doxygen{LBFGSOptimizerv4} optimizer with the \doxygen{LBFGSBOptimizerv4}. We
// made the modification because we found that LBFGS does not behave well when
// the starting position is at or close to optimal; instead we used LBFGSB in
// unconstrained mode.
//
//
// \index{itk::BSplineTransform}
// \index{itk::BSplineTransform!DeformableRegistration}
// \index{itk::LBFGSBOptimizerv4}
//
//
// Software Guide : EndLatex

#include "itkImageRegistrationMethodv4.h"
#include "itkMeanSquaresImageToImageMetricv4.h"

//  Software Guide : BeginLatex
//
//  The following are the most relevant headers to this example.
//
//  \index{itk::BSplineTransform!header}
//  \index{itk::LBFGSBOptimizerv4!header}
//
//  Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
#include "itkBSplineTransform.h"
#include "itkLBFGSBOptimizerv4.h"
// Software Guide : EndCodeSnippet

//  Software Guide : BeginLatex
//
//  The parameter space of the \code{BSplineTransform} is composed by
//  the set of all the deformations associated with the nodes of the BSpline
//  grid.  This large number of parameters enables it to represent a wide
//  variety of deformations, at the cost of requiring a
//  significant amount of computation time.
//
//  \index{itk::BSplineTransform!header}
//
//  Software Guide : EndLatex

#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"

#include "itkResampleImageFilter.h"
#include "itkCastImageFilter.h"
#include "itkSquaredDifferenceImageFilter.h"

#include "itkIdentityTransform.h"

#include "itkBSplineTransformInitializer.h"
#include "itkTransformToDisplacementFieldFilter.h"

//  The following section of code implements a Command observer
//  used to monitor the evolution of the registration process.
//
#include "itkCommand.h"
class CommandIterationUpdate : public itk::Command
{
public:
  using Self = CommandIterationUpdate;
  using Superclass = itk::Command;
  using Pointer = itk::SmartPointer<Self>;
  itkNewMacro( Self );

protected:
  CommandIterationUpdate() = default;

public:
  using OptimizerType = itk::LBFGSBOptimizerv4;
  using OptimizerPointer = const OptimizerType *;

  void Execute(itk::Object *caller, const itk::EventObject & event) override
  {
  Execute( (const itk::Object *)caller, event);
  }

  void Execute(const itk::Object * object, const itk::EventObject & event) override
  {
  auto optimizer = static_cast< OptimizerPointer >( object );
  if( !(itk::IterationEvent().CheckEvent( &event )) )
    {
    return;
    }
  std::cout << optimizer->GetCurrentIteration() << "   ";
  std::cout << optimizer->GetCurrentMetricValue() << "   ";
  std::cout << optimizer->GetInfinityNormOfProjectedGradient() << 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 outputImagefile  ";
    std::cerr << " [differenceOutputfile] [differenceBeforeRegistration] ";
    std::cerr << " [deformationField] ";
    return EXIT_FAILURE;
    }

  constexpr unsigned int ImageDimension = 3;
  using PixelType = float;

  using FixedImageType = itk::Image< PixelType, ImageDimension >;
  using MovingImageType = itk::Image< PixelType, ImageDimension >;


  //  Software Guide : BeginLatex
  //
  //  We instantiate now the type of the \code{BSplineTransform} using
  //  as template parameters the type for coordinates representation, the
  //  dimension of the space, and the order of the BSpline.
  //
  //  \index{BSplineTransform!New}
  //  \index{BSplineTransform!Instantiation}
  //
  //  Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  const unsigned int SpaceDimension = ImageDimension;
  constexpr unsigned int SplineOrder = 3;
  using CoordinateRepType = double;

  using TransformType = itk::BSplineTransform<
                            CoordinateRepType,
                            SpaceDimension,
                            SplineOrder >;
  // Software Guide : EndCodeSnippet


  using OptimizerType = itk::LBFGSBOptimizerv4;


  using MetricType = itk::MeanSquaresImageToImageMetricv4<
                                    FixedImageType,
                                    MovingImageType >;

  using RegistrationType = itk::ImageRegistrationMethodv4<
                                    FixedImageType,
                                    MovingImageType >;

  MetricType::Pointer         metric        = MetricType::New();
  OptimizerType::Pointer      optimizer     = OptimizerType::New();
  RegistrationType::Pointer   registration  = RegistrationType::New();


  registration->SetMetric(        metric        );
  registration->SetOptimizer(     optimizer     );


  using FixedImageReaderType = itk::ImageFileReader< FixedImageType  >;
  using MovingImageReaderType = itk::ImageFileReader< MovingImageType >;

  FixedImageReaderType::Pointer  fixedImageReader  = FixedImageReaderType::New();
  MovingImageReaderType::Pointer movingImageReader = MovingImageReaderType::New();

  fixedImageReader->SetFileName(  argv[1] );
  movingImageReader->SetFileName( argv[2] );

  FixedImageType::ConstPointer fixedImage = fixedImageReader->GetOutput();

  registration->SetFixedImage(  fixedImage   );
  registration->SetMovingImage(   movingImageReader->GetOutput()   );

  fixedImageReader->Update();

  //  Software Guide : BeginLatex
  //
  //  The transform object is constructed, initialized like previous examples
  //  and passed to the registration method.
  //
  //  \index{itk::ImageRegistrationMethodv4!SetInitialTransform()}
  //  \index{itk::ImageRegistrationMethodv4!InPlaceOn()}
  //
  //  Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  TransformType::Pointer  outputBSplineTransform = TransformType::New();
  // Software Guide : EndCodeSnippet

  // Initialize the transform
  using InitializerType = itk::BSplineTransformInitializer< TransformType,
                                            FixedImageType>;

  InitializerType::Pointer transformInitializer = InitializerType::New();

  unsigned int numberOfGridNodesInOneDimension = 8;

  TransformType::MeshSizeType             meshSize;
  meshSize.Fill( numberOfGridNodesInOneDimension - SplineOrder );

  transformInitializer->SetTransform( outputBSplineTransform );
  transformInitializer->SetImage( fixedImage );
  transformInitializer->SetTransformDomainMeshSize( meshSize );
  transformInitializer->InitializeTransform();

  // Set transform to identity
  using ParametersType = TransformType::ParametersType;
  const unsigned int numberOfParameters =
               outputBSplineTransform->GetNumberOfParameters();
  ParametersType parameters( numberOfParameters );
  parameters.Fill( 0.0 );
  outputBSplineTransform->SetParameters( parameters );

  // Software Guide : BeginCodeSnippet
  registration->SetInitialTransform( outputBSplineTransform );
  registration->InPlaceOn();
  // Software Guide : EndCodeSnippet

  //  A single level registration process is run using
  //  the shrink factor 1 and smoothing sigma 0.
  //
  constexpr unsigned int numberOfLevels = 1;

  RegistrationType::ShrinkFactorsArrayType shrinkFactorsPerLevel;
  shrinkFactorsPerLevel.SetSize( numberOfLevels );
  shrinkFactorsPerLevel[0] = 1;

  RegistrationType::SmoothingSigmasArrayType smoothingSigmasPerLevel;
  smoothingSigmasPerLevel.SetSize( numberOfLevels );
  smoothingSigmasPerLevel[0] = 0;

  registration->SetNumberOfLevels( numberOfLevels );
  registration->SetSmoothingSigmasPerLevel( smoothingSigmasPerLevel );
  registration->SetShrinkFactorsPerLevel( shrinkFactorsPerLevel );

  //  Software Guide : BeginLatex
  //
  //  Next we set the parameters of the LBFGSB Optimizer. Note that
  //  this optimizer does not support scales estimator and sets all
  //  the parameters scales to one.
  //  Also, we should set the boundary condition for each variable, where
  //  \code{boundSelect[i]} can be set as: \code{UNBOUNDED},
  //  \code{LOWERBOUNDED}, \code{BOTHBOUNDED}, \code{UPPERBOUNDED}.
  //
  //  Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  const unsigned int numParameters =
    outputBSplineTransform->GetNumberOfParameters();
  OptimizerType::BoundSelectionType boundSelect( numParameters );
  OptimizerType::BoundValueType upperBound( numParameters );
  OptimizerType::BoundValueType lowerBound( numParameters );

  boundSelect.Fill( OptimizerType::UNBOUNDED );
  upperBound.Fill( 0.0 );
  lowerBound.Fill( 0.0 );

  optimizer->SetBoundSelection( boundSelect );
  optimizer->SetUpperBound( upperBound );
  optimizer->SetLowerBound( lowerBound );

  optimizer->SetCostFunctionConvergenceFactor( 1e+12 );
  optimizer->SetGradientConvergenceTolerance( 1.0e-35 );
  optimizer->SetNumberOfIterations( 500 );
  optimizer->SetMaximumNumberOfFunctionEvaluations( 500 );
  optimizer->SetMaximumNumberOfCorrections( 5 );
  // Software Guide : EndCodeSnippet

  // Create the Command observer and register it with the optimizer.
  //
  CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
  optimizer->AddObserver( itk::IterationEvent(), observer );

  std::cout << "Starting Registration "
            << std::endl;

  try
    {
    registration->Update();
    std::cout << "Optimizer stop condition = "
              << registration->GetOptimizer()->GetStopConditionDescription()
              << std::endl;
    }
  catch( itk::ExceptionObject & err )
    {
    std::cerr << "ExceptionObject caught !" << std::endl;
    std::cerr << err << std::endl;
    return EXIT_FAILURE;
    }

  OptimizerType::ParametersType finalParameters =
                                      outputBSplineTransform->GetParameters();

  std::cout << "Last Transform Parameters" << std::endl;
  std::cout << finalParameters << std::endl;

  // Finally we use the last transform in order to resample the image.
  //
  using ResampleFilterType = itk::ResampleImageFilter<
                            MovingImageType,
                            FixedImageType >;

  ResampleFilterType::Pointer resample = ResampleFilterType::New();

  resample->SetTransform( outputBSplineTransform );
  resample->SetInput( movingImageReader->GetOutput() );

  resample->SetSize(    fixedImage->GetLargestPossibleRegion().GetSize() );
  resample->SetOutputOrigin(  fixedImage->GetOrigin() );
  resample->SetOutputSpacing( fixedImage->GetSpacing() );
  resample->SetOutputDirection( fixedImage->GetDirection() );
  resample->SetDefaultPixelValue( 100 );

  using OutputPixelType = unsigned char;

  using OutputImageType = itk::Image< OutputPixelType, ImageDimension >;

  using CastFilterType = itk::CastImageFilter<
                        FixedImageType,
                        OutputImageType >;

  using WriterType = itk::ImageFileWriter< OutputImageType >;


  WriterType::Pointer      writer =  WriterType::New();
  CastFilterType::Pointer  caster =  CastFilterType::New();


  writer->SetFileName( argv[3] );


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


  try
    {
    writer->Update();
    }
  catch( itk::ExceptionObject & err )
    {
    std::cerr << "ExceptionObject caught !" << std::endl;
    std::cerr << err << std::endl;
    return EXIT_FAILURE;
    }

  using DifferenceFilterType = itk::SquaredDifferenceImageFilter<
                                  FixedImageType,
                                  FixedImageType,
                                  OutputImageType >;

  DifferenceFilterType::Pointer difference = DifferenceFilterType::New();

  WriterType::Pointer writer2 = WriterType::New();
  writer2->SetInput( difference->GetOutput() );


  // Compute the difference image between the
  // fixed and resampled moving image.
  if( argc >= 5 )
    {
    difference->SetInput1( fixedImageReader->GetOutput() );
    difference->SetInput2( resample->GetOutput() );
    writer2->SetFileName( argv[4] );
    try
      {
      writer2->Update();
      }
    catch( itk::ExceptionObject & err )
      {
      std::cerr << "ExceptionObject caught !" << std::endl;
      std::cerr << err << std::endl;
      return EXIT_FAILURE;
      }
    }


  // Compute the difference image between the
  // fixed and moving image before registration.
  if( argc >= 6 )
    {
    writer2->SetFileName( argv[5] );
    difference->SetInput1( fixedImageReader->GetOutput() );
    difference->SetInput2( movingImageReader->GetOutput() );
    try
      {
      writer2->Update();
      }
    catch( itk::ExceptionObject & err )
      {
      std::cerr << "ExceptionObject caught !" << std::endl;
      std::cerr << err << std::endl;
      return EXIT_FAILURE;
      }
    }

  // Generate the explicit deformation field resulting from
  // the registration.
  using VectorPixelType = itk::Vector< float, ImageDimension >;
  using DisplacementFieldImageType = itk::Image< VectorPixelType, ImageDimension >;

  using DisplacementFieldGeneratorType = itk::TransformToDisplacementFieldFilter<
                        DisplacementFieldImageType,
                        CoordinateRepType >;

  DisplacementFieldGeneratorType::Pointer dispfieldGenerator =
                                                 DisplacementFieldGeneratorType::New();
  dispfieldGenerator->UseReferenceImageOn();
  dispfieldGenerator->SetReferenceImage( fixedImage );
  dispfieldGenerator->SetTransform( outputBSplineTransform );
  try
    {
    dispfieldGenerator->Update();
    }
  catch ( itk::ExceptionObject & err )
    {
    std::cerr << "Exception detected while generating deformation field";
    std::cerr << " : "  << err << std::endl;
    return EXIT_FAILURE;
    }

  using FieldWriterType = itk::ImageFileWriter< DisplacementFieldImageType >;
  FieldWriterType::Pointer fieldWriter = FieldWriterType::New();

  fieldWriter->SetInput( dispfieldGenerator->GetOutput() );

  if( argc >= 7 )
    {
    fieldWriter->SetFileName( argv[6] );
    try
      {
      fieldWriter->Update();
      }
    catch( itk::ExceptionObject & excp )
      {
      std::cerr << "Exception thrown " << std::endl;
      std::cerr << excp << std::endl;
      return EXIT_FAILURE;
      }
    }

  return EXIT_SUCCESS;
}