text: /*=========================================================================
   *
   *  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
   *
   *         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 itkGeodesicActiveContourLevelSetImageFilter_h
  #define itkGeodesicActiveContourLevelSetImageFilter_h
  
  #include "itkSegmentationLevelSetImageFilter.h"
  #include "itkGeodesicActiveContourLevelSetFunction.h"
  
  namespace itk
  {
  /** \class GeodesicActiveContourLevelSetImageFilter
   * \brief Segments structures in images based on a user supplied edge potential map.
   *
   * \par IMPORTANT
   * The SegmentationLevelSetImageFilter class and the
   * GeodesicActiveContourLevelSetFunction class contain additional information necessary
   * to gain full understanding of how to use this filter.
   *
   * \par OVERVIEW
   * This class is a level set method segmentation filter. An initial contour
   * is propagated outwards (or inwards) until it ''sticks'' to the shape boundaries.
   * This is done by using a level set speed function based on a user supplied
   * edge potential map.
   *
   * \par INPUTS
   * This filter requires two inputs. The first input is a initial level set.
   * The initial level set is a real image which contains the initial contour/surface
   * as the zero level set. For example, a signed distance function from the initial
   * contour/surface is typically used. Unlike the simpler ShapeDetectionLevelSetImageFilter
   * the initial contour does not have to lie wholly within the shape to be segmented.
   * The initial contour is allow to overlap the shape boundary. The extra advection term
   * in the update equation behaves like a doublet and attracts the contour to the boundary.
   * This approach for segmentation follows that of Caselles et al (1997).
   *
   * \par
   * The second input is the feature image. For this filter, this is the edge
   * potential map. General characteristics of an edge potential map is that
   * it has values close to zero in regions near the edges and values close
   * to one inside the shape itself. Typically, the edge potential map is compute
   * from the image gradient, for example:
   *
   * \f[ g(I) = 1 / ( 1 + | (\nabla * G)(I)| ) \f]
   * \f[ g(I) = \exp^{-|(\nabla * G)(I)|} \f]
   *
   * where \f$ I \f$ is image intensity and
   * \f$ (\nabla * G) \f$ is the derivative of Gaussian operator.
   *
   * \par
   * See SegmentationLevelSetImageFilter and SparseFieldLevelSetImageFilter
   * for more information on Inputs.
   *
   * \par PARAMETERS
   * The PropagationScaling parameter can be used to switch from propagation outwards
   * (POSITIVE scaling parameter) versus propagating inwards (NEGATIVE scaling
   * parameter).
   *
   * This implementation allows the user to set the weights between the propagation, advection
   * and curvature term using methods SetPropagationScaling(), SetAdvectionScaling(),
   * SetCurvatureScaling(). In general, the larger the CurvatureScaling, the smoother the
   * resulting contour. To follow the implementation in Caselles et al paper,
   * set the PropagationScaling to \f$ c \f$ (the inflation or ballon force) and
   * AdvectionScaling and CurvatureScaling both to 1.0.
   *
   * \par OUTPUTS
   * The filter outputs a single, scalar, real-valued image.
   * Negative values in the output image represent the inside of the segmented region
   * and positive values in the image represent the outside of the segmented region.  The
   * zero crossings of the image correspond to the position of the propagating
   * front.
   *
   * \par
   * See SparseFieldLevelSetImageFilter and
   * SegmentationLevelSetImageFilter for more information.
   *
   * \par REFERENCES
   * \par
   *    "Geodesic Active Contours",
   *    V. Caselles, R. Kimmel and G. Sapiro.
   *    International Journal on Computer Vision,
   *    Vol 22, No. 1, pp 61-97, 1997
   *
   * \sa SegmentationLevelSetImageFilter
   * \sa GeodesicActiveContourLevelSetFunction
   * \sa SparseFieldLevelSetImageFilter
   *
   * \ingroup LevelSetSegmentation
   * \ingroup ITKLevelSets
   */
  template <typename TInputImage, typename TFeatureImage, typename TOutputPixelType = float>
  class ITK_TEMPLATE_EXPORT GeodesicActiveContourLevelSetImageFilter
    : public SegmentationLevelSetImageFilter<TInputImage, TFeatureImage, TOutputPixelType>
  {
  public:
    ITK_DISALLOW_COPY_AND_ASSIGN(GeodesicActiveContourLevelSetImageFilter);
  
    /** Standard class type aliases */
    using Self = GeodesicActiveContourLevelSetImageFilter;
    using Superclass = SegmentationLevelSetImageFilter<TInputImage, TFeatureImage, TOutputPixelType>;
  
    using Pointer = SmartPointer<Self>;
    using ConstPointer = SmartPointer<const Self>;
  
    /** Inherited type alias from the superclass. */
    using ValueType = typename Superclass::ValueType;
    using OutputImageType = typename Superclass::OutputImageType;
    using FeatureImageType = typename Superclass::FeatureImageType;
  
    /** Type of the segmentation function */
    using GeodesicActiveContourFunctionType = GeodesicActiveContourLevelSetFunction<OutputImageType, FeatureImageType>;
    using GeodesicActiveContourFunctionPointer = typename GeodesicActiveContourFunctionType::Pointer;
  
    /** Run-time type information (and related methods). */
    itkTypeMacro(GeodesicActiveContourLevelSetImageFilter, SegmentationLevelSetImageFilter);
  
    /** Method for creation through the object factory */
    itkNewMacro(Self);
  
    /** Set the value of sigma used to compute the edge potential map
     * derivatives  */
    void
    SetDerivativeSigma(float value)
    {
      if (Math::NotExactlyEquals(value, m_GeodesicActiveContourFunction->GetDerivativeSigma()))
      {
        m_GeodesicActiveContourFunction->SetDerivativeSigma(value);
        this->Modified();
      }
    }
  
    /** Get the value of sigma used to compute the edge potential map derivatives.
     */
    float
    GetDerivativeSigma() const
    {
      return m_GeodesicActiveContourFunction->GetDerivativeSigma();
    }
  
  protected:
    ~GeodesicActiveContourLevelSetImageFilter() override = default;
    GeodesicActiveContourLevelSetImageFilter();
  
    void
    PrintSelf(std::ostream & os, Indent indent) const override;
  
    /** Overridden from Superclass to handle the case when PropagationScaling is
      zero.*/
    void
    GenerateData() override;
  
  private:
    GeodesicActiveContourFunctionPointer m_GeodesicActiveContourFunction;
  };
  } // end namespace itk
  
  #ifndef ITK_MANUAL_INSTANTIATION
  #  include "itkGeodesicActiveContourLevelSetImageFilter.hxx"
  #endif
  
  #endif
  