SphinxExamples/src/Core/Transform/GlobalRegistrationTwoImagesBSpline/Code.cxx

/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         https://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
 *
 *=========================================================================*/
#include "itkImageRegistrationMethod.h"
#include "itkMeanSquaresImageToImageMetric.h"
#include "itkTimeProbesCollectorBase.h"
#include "itkSpatialObjectToImageFilter.h"
#include "itkEllipseSpatialObject.h"
 
#include "itkBSplineTransform.h"
#include "itkLBFGSOptimizer.h"
#include "itkImageFileWriter.h"
#include "itkResampleImageFilter.h"
#include "itkCastImageFilter.h"
 
#ifdef ENABLE_QUICKVIEW
#  include "QuickView.h"
#endif
 
constexpr unsigned int ImageDimension = 2;
using PixelType = float;
 
using ImageType = itk::Image<PixelType, ImageDimension>;
 
static void
CreateEllipseImage(const ImageType::Pointer & image);
static void
CreateCircleImage(const ImageType::Pointer & image);
 
int
main(int itkNotUsed(argc), char * itkNotUsed(argv)[])
{
 
  const unsigned int     SpaceDimension = ImageDimension;
  constexpr unsigned int SplineOrder = 3;
  using CoordinateRepType = double;
 
  using TransformType = itk::BSplineTransform<CoordinateRepType, SpaceDimension, SplineOrder>;
  using OptimizerType = itk::LBFGSOptimizer;
 
 
  using MetricType = itk::MeanSquaresImageToImageMetric<ImageType, ImageType>;
 
  using InterpolatorType = itk::LinearInterpolateImageFunction<ImageType, double>;
 
  using RegistrationType = itk::ImageRegistrationMethod<ImageType, ImageType>;
 
  auto metric = MetricType::New();
  auto optimizer = OptimizerType::New();
  auto interpolator = InterpolatorType::New();
  auto registration = RegistrationType::New();
 
 
  // The old registration framework has problems with multi-threading
  // For now, we set the number of work units to 1
  registration->SetNumberOfWorkUnits(1);
 
  registration->SetMetric(metric);
  registration->SetOptimizer(optimizer);
  registration->SetInterpolator(interpolator);
 
  auto transform = TransformType::New();
  registration->SetTransform(transform);
 
  // Create the synthetic images
  auto fixedImage = ImageType::New();
  CreateCircleImage(fixedImage);
 
  auto movingImage = ImageType::New();
  CreateEllipseImage(movingImage);
 
  // Setup the registration
  registration->SetFixedImage(fixedImage);
  registration->SetMovingImage(movingImage);
 
  ImageType::RegionType fixedRegion = fixedImage->GetBufferedRegion();
  registration->SetFixedImageRegion(fixedRegion);
 
  //  Here we define the parameters of the BSplineDeformableTransform grid.  We
  //  arbitrarily decide to use a grid with $5 \times 5$ nodes within the image.
  //  The reader should note that the BSpline computation requires a
  //  finite support region ( 1 grid node at the lower borders and 2
  //  grid nodes at upper borders). Therefore in this example, we set
  //  the grid size to be $8 \times 8$ and place the grid origin such that
  //  grid node (1,1) coincides with the first pixel in the fixed image.
 
  TransformType::PhysicalDimensionsType fixedPhysicalDimensions;
  TransformType::MeshSizeType           meshSize;
  for (unsigned int i = 0; i < ImageDimension; ++i)
  {
    fixedPhysicalDimensions[i] =
      fixedImage->GetSpacing()[i] * static_cast<double>(fixedImage->GetLargestPossibleRegion().GetSize()[i] - 1);
  }
  unsigned int numberOfGridNodesInOneDimension = 5;
  meshSize.Fill(numberOfGridNodesInOneDimension - SplineOrder);
  transform->SetTransformDomainOrigin(fixedImage->GetOrigin());
  transform->SetTransformDomainPhysicalDimensions(fixedPhysicalDimensions);
  transform->SetTransformDomainMeshSize(meshSize);
  transform->SetTransformDomainDirection(fixedImage->GetDirection());
 
  using ParametersType = TransformType::ParametersType;
 
  const unsigned int numberOfParameters = transform->GetNumberOfParameters();
 
  ParametersType parameters(numberOfParameters);
 
  parameters.Fill(0.0);
 
  transform->SetParameters(parameters);
 
  //  We now pass the parameters of the current transform as the initial
  //  parameters to be used when the registration process starts.
 
  registration->SetInitialTransformParameters(transform->GetParameters());
 
  std::cout << "Intial Parameters = " << std::endl;
  std::cout << transform->GetParameters() << std::endl;
 
  //  Next we set the parameters of the LBFGS Optimizer.
 
  optimizer->SetGradientConvergenceTolerance(0.05);
  optimizer->SetLineSearchAccuracy(0.9);
  optimizer->SetDefaultStepLength(.5);
  optimizer->TraceOn();
  optimizer->SetMaximumNumberOfFunctionEvaluations(1000);
 
  std::cout << std::endl << "Starting Registration" << std::endl;
 
  try
  {
    registration->Update();
    std::cout << "Optimizer stop condition = " << registration->GetOptimizer()->GetStopConditionDescription()
              << std::endl;
  }
  catch (const itk::ExceptionObject & err)
  {
    std::cerr << "ExceptionObject caught !" << std::endl;
    std::cerr << err << std::endl;
    return EXIT_FAILURE;
  }
 
  OptimizerType::ParametersType finalParameters = registration->GetLastTransformParameters();
 
  std::cout << "Last Transform Parameters" << std::endl;
  std::cout << finalParameters << std::endl;
 
  transform->SetParameters(finalParameters);
 
  using ResampleFilterType = itk::ResampleImageFilter<ImageType, ImageType>;
 
  auto resample = ResampleFilterType::New();
 
  resample->SetTransform(transform);
  resample->SetInput(movingImage);
 
  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<ImageType, OutputImageType>;
 
  auto caster = CastFilterType::New();
  caster->SetInput(resample->GetOutput());
 
  try
  {
    itk::WriteImage(caster->GetOutput(), "output.png");
  }
  catch (const itk::ExceptionObject & err)
  {
    std::cerr << "ExceptionObject caught !" << std::endl;
    std::cerr << err << std::endl;
    return EXIT_FAILURE;
  }
 
#ifdef ENABLE_QUICKVIEW
  QuickView viewer;
  viewer.AddImage(fixedImage.GetPointer(), true, "Fixed Image");
  viewer.AddImage(movingImage.GetPointer(), true, "Moving Image");
  viewer.AddImage(resample->GetOutput(), true, "Resampled Moving Image");
 
  viewer.Visualize();
#endif
 
  return EXIT_SUCCESS;
}
 
void
CreateEllipseImage(const ImageType::Pointer & image)
{
  using EllipseType = itk::EllipseSpatialObject<ImageDimension>;
 
  using SpatialObjectToImageFilterType = itk::SpatialObjectToImageFilter<EllipseType, ImageType>;
 
  auto imageFilter = SpatialObjectToImageFilterType::New();
 
  ImageType::SizeType size;
  size[0] = 100;
  size[1] = 100;
 
  imageFilter->SetSize(size);
 
  ImageType::SpacingType spacing;
  spacing.Fill(1);
  imageFilter->SetSpacing(spacing);
 
  auto                   ellipse = EllipseType::New();
  EllipseType::ArrayType radiusArray;
  radiusArray[0] = 10;
  radiusArray[1] = 20;
  ellipse->SetRadiusInObjectSpace(radiusArray);
 
  using TransformType = EllipseType::TransformType;
  auto transform = TransformType::New();
  transform->SetIdentity();
 
  TransformType::OutputVectorType translation;
  translation[0] = 65;
  translation[1] = 45;
  transform->Translate(translation, false);
 
  ellipse->SetObjectToParentTransform(transform);
 
  imageFilter->SetInput(ellipse);
 
  ellipse->SetDefaultInsideValue(255);
  ellipse->SetDefaultOutsideValue(0);
  imageFilter->SetUseObjectValue(true);
  imageFilter->SetOutsideValue(0);
 
  imageFilter->Update();
 
  image->Graft(imageFilter->GetOutput());
}
 
void
CreateCircleImage(const ImageType::Pointer & image)
{
  using EllipseType = itk::EllipseSpatialObject<ImageDimension>;
 
  using SpatialObjectToImageFilterType = itk::SpatialObjectToImageFilter<EllipseType, ImageType>;
 
  auto imageFilter = SpatialObjectToImageFilterType::New();
 
  ImageType::SizeType size;
  size[0] = 100;
  size[1] = 100;
 
  imageFilter->SetSize(size);
 
  ImageType::SpacingType spacing;
  spacing.Fill(1);
  imageFilter->SetSpacing(spacing);
 
  auto                   ellipse = EllipseType::New();
  EllipseType::ArrayType radiusArray;
  radiusArray[0] = 10;
  radiusArray[1] = 10;
  ellipse->SetRadiusInObjectSpace(radiusArray);
 
  using TransformType = EllipseType::TransformType;
  auto transform = TransformType::New();
  transform->SetIdentity();
 
  TransformType::OutputVectorType translation;
  translation[0] = 50;
  translation[1] = 50;
  transform->Translate(translation, false);
 
  ellipse->SetObjectToParentTransform(transform);
 
  imageFilter->SetInput(ellipse);
 
  ellipse->SetDefaultInsideValue(255);
  ellipse->SetDefaultOutsideValue(0);
  imageFilter->SetUseObjectValue(true);
  imageFilter->SetOutsideValue(0);
 
  imageFilter->Update();
 
  image->Graft(imageFilter->GetOutput());
}