rtkConjugateGradientConeBeamReconstructionFilter.h

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 *  Copyright RTK Consortium
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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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 *  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
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#ifndef rtkConjugateGradientConeBeamReconstructionFilter_h
#define rtkConjugateGradientConeBeamReconstructionFilter_h

#include <itkMultiplyImageFilter.h>
#include <itkDivideOrZeroOutImageFilter.h>
#include <itkProcessObject.h>
#include <itkObject.h>
#include <itkCommand.h>
#include <itkIterationReporter.h>

#include "rtkConjugateGradientImageFilter.h"
#include "rtkReconstructionConjugateGradientOperator.h"
#include "rtkIterativeConeBeamReconstructionFilter.h"
#include "rtkThreeDCircularProjectionGeometry.h"
#include "rtkDisplacedDetectorImageFilter.h"
#include "rtkConstantImageSource.h"
#include "rtkLaplacianImageFilter.h"
#include "rtkBlockDiagonalMatrixVectorMultiplyImageFilter.h"

#ifdef RTK_USE_CUDA
#  include "rtkCudaConjugateGradientImageFilter.h"
#  include "rtkCudaDisplacedDetectorImageFilter.h"
#  include "rtkCudaConstantVolumeSource.h"
#endif

namespace rtk
{
template <typename TOutputImage, typename TSingleComponentImage = TOutputImage, typename TWeightsImage = TOutputImage>
class ITK_TEMPLATE_EXPORT ConjugateGradientConeBeamReconstructionFilter
  : public IterativeConeBeamReconstructionFilter<TOutputImage>
{
public:
  ITK_DISALLOW_COPY_AND_MOVE(ConjugateGradientConeBeamReconstructionFilter);

  using Self = ConjugateGradientConeBeamReconstructionFilter;
  using Superclass = IterativeConeBeamReconstructionFilter<TOutputImage>;
  using Pointer = itk::SmartPointer<Self>;

  itkNewMacro(Self);

  itkOverrideGetNameOfClassMacro(ConjugateGradientConeBeamReconstructionFilter);

  void
  SetInputVolume(const TOutputImage * vol);
  void
  SetInputProjectionStack(const TOutputImage * projs);
  void
  SetInputWeights(const TWeightsImage * weights);
  void
  SetLocalRegularizationWeights(const TSingleComponentImage * weights);

  using ForwardProjectionFilterType = ForwardProjectionImageFilter<TOutputImage, TOutputImage>;
  using ForwardProjectionFilterPointer = typename ForwardProjectionFilterType::Pointer;
  using BackProjectionFilterType = BackProjectionImageFilter<TOutputImage, TOutputImage>;
  using ConjugateGradientFilterType = ConjugateGradientImageFilter<TOutputImage>;
  using ConjugateGradientFilterPointer = typename ConjugateGradientFilterType::Pointer;
  using MultiplyFilterType = itk::MultiplyImageFilter<TOutputImage, TSingleComponentImage, TOutputImage>;
  using CGOperatorFilterType =
    ReconstructionConjugateGradientOperator<TOutputImage, TSingleComponentImage, TWeightsImage>;
  using DivideFilterType = itk::DivideOrZeroOutImageFilter<TOutputImage>;
  using StatisticsImageFilterType = itk::StatisticsImageFilter<TOutputImage>;
  using OutputImagePointer = typename TOutputImage::Pointer;
  using StatisticsFilterType = itk::StatisticsImageFilter<TSingleComponentImage>;

  using ForwardProjectionType = typename Superclass::ForwardProjectionType;
  using BackProjectionType = typename Superclass::BackProjectionType;

  // If TOutputImage is an itk::Image of floats or double, so are the weights, and a simple Multiply filter is required
  // If TOutputImage is an itk::Image of itk::Vector<float (or double)>, a BlockDiagonalMatrixVectorMultiply filter
  // is needed. Thus the meta-programming construct
  using MatrixVectorMultiplyFilterType = BlockDiagonalMatrixVectorMultiplyImageFilter<TOutputImage, TWeightsImage>;
  using PlainMultiplyFilterType = itk::MultiplyImageFilter<TOutputImage, TOutputImage, TOutputImage>;
  using MultiplyWithWeightsFilterType = typename std::conditional_t<std::is_same_v<TSingleComponentImage, TOutputImage>,
                                                                    PlainMultiplyFilterType,
                                                                    MatrixVectorMultiplyFilterType>;
  using CPUOutputImageType = typename itk::Image<typename TOutputImage::PixelType, TOutputImage::ImageDimension>;
#ifdef RTK_USE_CUDA
  using DisplacedDetectorFilterType = typename std::conditional_t<!std::is_same_v<TOutputImage, CPUOutputImageType> &&
                                                                    std::is_same_v<TSingleComponentImage, TOutputImage>,
                                                                  CudaDisplacedDetectorImageFilter,
                                                                  DisplacedDetectorImageFilter<TWeightsImage>>;
  using ConstantImageSourceType = typename std::conditional_t<!std::is_same_v<TOutputImage, CPUOutputImageType> &&
                                                                std::is_same_v<TSingleComponentImage, TOutputImage>,
                                                              CudaConstantVolumeSource,
                                                              ConstantImageSource<TOutputImage>>;
  using ConstantWeightSourceType = typename std::conditional_t<!std::is_same_v<TOutputImage, CPUOutputImageType> &&
                                                                 std::is_same_v<TSingleComponentImage, TOutputImage>,
                                                               CudaConstantVolumeSource,
                                                               ConstantImageSource<TWeightsImage>>;
#else
  using DisplacedDetectorFilterType = DisplacedDetectorImageFilter<TWeightsImage>;
  using ConstantImageSourceType = ConstantImageSource<TOutputImage>;
  using ConstantWeightSourceType = ConstantImageSource<TWeightsImage>;
#endif

  void
  SetSupportMask(const TSingleComponentImage * SupportMask);
  typename TSingleComponentImage::ConstPointer
  GetSupportMask();

  itkSetConstObjectMacro(Geometry, ThreeDCircularProjectionGeometry);

  itkSetMacro(NumberOfIterations, int);
  itkGetMacro(NumberOfIterations, int);

  itkSetMacro(DisableDisplacedDetectorFilter, bool);
  itkGetMacro(DisableDisplacedDetectorFilter, bool);

  itkSetMacro(Tikhonov, float);
  itkGetMacro(Tikhonov, float);

  itkSetMacro(Gamma, float);
  itkGetMacro(Gamma, float);

  itkGetMacro(CudaConjugateGradient, bool);
  itkSetMacro(CudaConjugateGradient, bool);

protected:
  ConjugateGradientConeBeamReconstructionFilter();
  ~ConjugateGradientConeBeamReconstructionFilter() override = default;

  void
  VerifyPreconditions() const override;

  void
  GenerateData() override;

  typename MultiplyFilterType::Pointer                                       m_MultiplyProjectionsFilter;
  typename MultiplyFilterType::Pointer                                       m_MultiplyVolumeFilter;
  typename MultiplyFilterType::Pointer                                       m_MultiplyOutputFilter;
  ConjugateGradientFilterPointer                                             m_ConjugateGradientFilter;
  typename CGOperatorFilterType::Pointer                                     m_CGOperator;
  typename ForwardProjectionImageFilter<TOutputImage, TOutputImage>::Pointer m_ForwardProjectionFilter;
  typename BackProjectionImageFilter<TOutputImage, TOutputImage>::Pointer    m_BackProjectionFilter;
  typename BackProjectionImageFilter<TOutputImage, TOutputImage>::Pointer    m_BackProjectionFilterForB;
  typename DisplacedDetectorFilterType::Pointer                              m_DisplacedDetectorFilter;
  typename ConstantImageSourceType::Pointer                                  m_ConstantVolumeSource;
  typename MultiplyWithWeightsFilterType::Pointer                            m_MultiplyWithWeightsFilter;

  void
  VerifyInputInformation() const override
  {}

  void
  GenerateInputRequestedRegion() override;
  void
  GenerateOutputInformation() override;

  typename TOutputImage::ConstPointer
  GetInputVolume();
  typename TOutputImage::ConstPointer
  GetInputProjectionStack();
  typename TWeightsImage::ConstPointer
  GetInputWeights();
  typename TSingleComponentImage::ConstPointer
  GetLocalRegularizationWeights();

  template <typename ImageType,
            typename IterativeConeBeamReconstructionFilter<TOutputImage>::template EnableCudaScalarAndVectorType<
              ImageType> * = nullptr>
  ConjugateGradientFilterPointer
  InstantiateCudaConjugateGradientImageFilter();

  template <typename ImageType,
            typename IterativeConeBeamReconstructionFilter<TOutputImage>::template DisableCudaScalarAndVectorType<
              ImageType> * = nullptr>
  ConjugateGradientFilterPointer
  InstantiateCudaConjugateGradientImageFilter();

  void
  ReportProgress(itk::Object *, const itk::EventObject &);

private:
  ThreeDCircularProjectionGeometry::ConstPointer m_Geometry;

  int   m_NumberOfIterations;
  float m_Gamma;
  float m_Tikhonov;
  bool  m_CudaConjugateGradient;
  bool  m_DisableDisplacedDetectorFilter;

  // Iteration reporting
  itk::IterationReporter m_IterationReporter;
};
} // namespace rtk


#ifndef ITK_MANUAL_INSTANTIATION
#  include "rtkConjugateGradientConeBeamReconstructionFilter.hxx"
#endif

#endif