itkSegmentationLevelSetImageFilter.h

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/*=========================================================================
 *
 *  Copyright Insight Software Consortium
 *
 *  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
 *
 *         http://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.
 *
 *=========================================================================*/
#ifndef itkSegmentationLevelSetImageFilter_h
#define itkSegmentationLevelSetImageFilter_h

#include "itkSparseFieldLevelSetImageFilter.h"
#include "itkSegmentationLevelSetFunction.h"
#include "itkMath.h"

namespace itk
{
template< typename TInputImage,
          typename TFeatureImage,
          typename TOutputPixelType = float >
class ITK_TEMPLATE_EXPORT SegmentationLevelSetImageFilter:
  public SparseFieldLevelSetImageFilter< TInputImage, Image< TOutputPixelType,
                                                             TInputImage::ImageDimension > >
{
public:
  ITK_DISALLOW_COPY_AND_ASSIGN(SegmentationLevelSetImageFilter);

  using Self = SegmentationLevelSetImageFilter;

  //static constexpr unsigned int InputImageDimension = TInputImage::ImageDimension;

  using OutputImageType = Image< TOutputPixelType, Self::InputImageDimension >;

  using Superclass = SparseFieldLevelSetImageFilter< TInputImage, OutputImageType >;
  using Pointer = SmartPointer< Self >;
  using ConstPointer = SmartPointer< const Self >;

  using ValueType = typename Superclass::ValueType;
  using IndexType = typename Superclass::IndexType;
  using TimeStepType = typename Superclass::TimeStepType;
  using InputImageType = typename Superclass::InputImageType;

  using FeatureImageType = TFeatureImage;

  using SegmentationFunctionType =
      SegmentationLevelSetFunction< OutputImageType, FeatureImageType >;

  using VectorImageType = typename SegmentationFunctionType::VectorImageType;
  using SpeedImageType = typename SegmentationFunctionType::ImageType;

  itkTypeMacro(SegmentationLevelSetImageFilter, SparseFieldLevelSetImageFilter);

  void SetMaximumIterations(unsigned int i)
  {
    itkWarningMacro("SetMaximumIterations is deprecated.  Please use SetNumberOfIterations instead.");
    this->SetNumberOfIterations(i);
  }

  unsigned int GetMaximumIterations()
  {
    itkWarningMacro("GetMaximumIterations is deprecated. Please use GetNumberOfIterations instead.");
    return this->GetNumberOfIterations();
  }

  virtual void SetFeatureImage(const FeatureImageType *f)
    {
      itkDebugMacro("setting input FeatureImage to " << f );
      if ( f != itkDynamicCastInDebugMode< FeatureImageType * >( this->ProcessObject::GetInput("FeatureImage") ) )
        {
        this->ProcessObject::SetInput( "FeatureImage", const_cast< FeatureImageType * >( f ) );
        m_SegmentationFunction->SetFeatureImage(f);
        this->Modified();
        }
    }
  itkGetInputMacro(FeatureImage, FeatureImageType);

  itkSetInputMacro(InitialImage, InputImageType);
  itkGetInputMacro(InitialImage, InputImageType);

  void SetInput2(const FeatureImageType *input)
  {
    this->SetFeatureImage(input);
  }

  void SetSpeedImage(SpeedImageType *s)
  {  m_SegmentationFunction->SetSpeedImage(s); }

  void SetAdvectionImage(VectorImageType *v)
  { m_SegmentationFunction->SetAdvectionImage(v); }

  virtual const SpeedImageType * GetSpeedImage() const
  { return m_SegmentationFunction->GetSpeedImage(); }

  virtual const VectorImageType * GetAdvectionImage() const
  { return m_SegmentationFunction->GetAdvectionImage(); }

  void SetUseNegativeFeaturesOn()
  {
    itkWarningMacro(
      << "SetUseNegativeFeaturesOn has been deprecated.  Please use ReverseExpansionDirectionOn() instead");
    this->ReverseExpansionDirectionOn();
  }

  void SetUseNegativeFeaturesOff()
  {
    itkWarningMacro(
      << "SetUseNegativeFeaturesOff has been deprecated.  Please use ReverseExpansionDirectionOff() instead");
    this->ReverseExpansionDirectionOff();
  }

  void SetUseNegativeFeatures(bool u)
  {
    itkWarningMacro(<< "SetUseNegativeFeatures has been deprecated.  Please use SetReverseExpansionDirection instead");
    if ( u == true )
      {
      this->SetReverseExpansionDirection(false);
      }
    else
      {
      this->SetReverseExpansionDirection(true);
      }
  }

  bool GetUseNegativeFeatures() const
  {
    itkWarningMacro(<< "GetUseNegativeFeatures has been deprecated.  Please use GetReverseExpansionDirection() instead");
    if ( m_ReverseExpansionDirection == false )
      {
      return true;
      }
    else
      {
      return false;
      }
  }

  itkSetMacro(ReverseExpansionDirection, bool);
  itkGetConstMacro(ReverseExpansionDirection, bool);
  itkBooleanMacro(ReverseExpansionDirection);

  itkSetMacro(AutoGenerateSpeedAdvection, bool);
  itkGetConstMacro(AutoGenerateSpeedAdvection, bool);
  itkBooleanMacro(AutoGenerateSpeedAdvection);

  void SetFeatureScaling(ValueType v)
  {
    if ( Math::NotExactlyEquals(v, m_SegmentationFunction->GetPropagationWeight()) )
      {
      this->SetPropagationScaling(v);
      }
    if ( Math::NotExactlyEquals(v, m_SegmentationFunction->GetAdvectionWeight()) )
      {
      this->SetAdvectionScaling(v);
      }
  }

  void SetPropagationScaling(ValueType v)
  {
    if ( Math::NotExactlyEquals(v, m_SegmentationFunction->GetPropagationWeight()) )
      {
      m_SegmentationFunction->SetPropagationWeight(v);
      this->Modified();
      }
  }

  ValueType GetPropagationScaling() const
  {
    return m_SegmentationFunction->GetPropagationWeight();
  }

  void SetAdvectionScaling(ValueType v)
  {
    if ( Math::NotExactlyEquals(v, m_SegmentationFunction->GetAdvectionWeight()) )
      {
      m_SegmentationFunction->SetAdvectionWeight(v);
      this->Modified();
      }
  }

  ValueType GetAdvectionScaling() const
  {
    return m_SegmentationFunction->GetAdvectionWeight();
  }

  void SetCurvatureScaling(ValueType v)
  {
    if ( Math::NotExactlyEquals(v, m_SegmentationFunction->GetCurvatureWeight()) )
      {
      m_SegmentationFunction->SetCurvatureWeight(v);
      this->Modified();
      }
  }

  ValueType GetCurvatureScaling() const
  {
    return m_SegmentationFunction->GetCurvatureWeight();
  }

  void SetUseMinimalCurvature(bool b)
  {
    if ( m_SegmentationFunction->GetUseMinimalCurvature() != b )
      {
      m_SegmentationFunction->SetUseMinimalCurvature(b);
      this->Modified();
      }
  }

  bool GetUseMinimalCurvature() const
  {
    return m_SegmentationFunction->GetUseMinimalCurvature();
  }

  void UseMinimalCurvatureOn()
  {
    this->SetUseMinimalCurvature(true);
  }

  void UseMinimalCurvatureOff()
  {
    this->SetUseMinimalCurvature(false);
  }

  virtual void SetSegmentationFunction(SegmentationFunctionType *s)
  {
    m_SegmentationFunction = s;

    typename SegmentationFunctionType::RadiusType r;
    r.Fill(1);

    m_SegmentationFunction->Initialize(r);
    this->SetDifferenceFunction(m_SegmentationFunction);
    this->Modified();
  }

  virtual SegmentationFunctionType * GetSegmentationFunction()
  { return m_SegmentationFunction; }

  void SetMaximumCurvatureTimeStep(double n)
  {
    if ( n != m_SegmentationFunction->GetMaximumCurvatureTimeStep() )
      {
      m_SegmentationFunction->SetMaximumCurvatureTimeStep(n);
      this->Modified();
      }
  }

  double GetMaximumCurvatureTimeStep() const
  {
    return m_SegmentationFunction->GetMaximumCurvatureTimeStep();
  }

  void SetMaximumPropagationTimeStep(double n)
  {
    if ( n != m_SegmentationFunction->GetMaximumPropagationTimeStep() )
      {
      m_SegmentationFunction->SetMaximumPropagationTimeStep(n);
      this->Modified();
      }
  }

  double GetMaximumPropagationTimeStep() const
  {
    return m_SegmentationFunction->GetMaximumPropagationTimeStep();
  }

  void GenerateSpeedImage();

  void GenerateAdvectionImage();

#ifdef ITK_USE_CONCEPT_CHECKING
  // Begin concept checking
  itkConceptMacro( OutputHasNumericTraitsCheck,
                   ( Concept::HasNumericTraits< TOutputPixelType > ) );
  // End concept checking
#endif

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

  void PrintSelf(std::ostream & os, Indent indent) const override;

  void InitializeIteration() override
  {
    Superclass::InitializeIteration();
    // Estimate the progress of the filter
    this->UpdateProgress( (float)( (float)this->GetElapsedIterations()
                                / (float)this->GetNumberOfIterations() ) );
  }

  void GenerateData() override;

  bool m_ReverseExpansionDirection;

  bool m_AutoGenerateSpeedAdvection;

private:
  SegmentationFunctionType *m_SegmentationFunction;
};
} // end namespace itk

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

#endif