libinsighttoolkit4-dev 4.5.0-3 / usr / include / ITK-4.5 / itkKappaStatisticImageToImageMetric.h

/*=========================================================================
 *
 *  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 __itkKappaStatisticImageToImageMetric_h
#define __itkKappaStatisticImageToImageMetric_h

#include "itkImageToImageMetric.h"

namespace itk
{
/** \class KappaStatisticImageToImageMetric
 * \brief Computes similarity between two binary objects to be
 * registered
 *
 * This Class is templated over the type of the fixed and moving
 * images to be compared.  The metric here is designed for matching
 * pixels in two images with the same exact value.  Only one value can
 * be considered (the default is 255) and can be specified with the
 * SetForegroundValue method.  In the computation of the metric, only
 * foreground pixels are considered.  The metric value is given
 * by 2*|A&B|/(|A|+|B|), where A is the foreground region in the moving
 * image, B is the foreground region in the fixed image, & is intersection,
 * and |.| indicates the area of the enclosed set.  The metric is
 * described in "Morphometric Analysis of White Matter Lesions in MR
 * Images: Method and Validation", A. P. Zijdenbos, B. M. Dawant, R. A.
 * Margolin, A. C. Palmer.
 *
 * This metric is especially useful when considering the similarity between
 * binary images.  Given the nature of binary images, a nearest neighbor
 * interpolator is the preferred interpolator.
 *
 * Metric values range from 0.0 (no foreground alignment) to 1.0
 * (perfect foreground alignment).  When dealing with optimizers that can
 * only minimize a metric, use the ComplementOn() method.
 *
 * \ingroup RegistrationMetrics
 * \ingroup ITKRegistrationCommon
 */
template< typename TFixedImage, typename TMovingImage >
class KappaStatisticImageToImageMetric:
  public ImageToImageMetric< TFixedImage, TMovingImage >
{
public:

  /** Standard class typedefs. */
  typedef KappaStatisticImageToImageMetric                Self;
  typedef ImageToImageMetric< TFixedImage, TMovingImage > Superclass;
  typedef SmartPointer< Self >                            Pointer;
  typedef SmartPointer< const Self >                      ConstPointer;

  /** Method for creation through the object factory. */
  itkNewMacro(Self);

  /** Run-time type information (and related methods). */
  itkTypeMacro(KappaStatisticImageToImageMetric, ImageToImageMetric);

  /** Types transferred from the base class */
  typedef typename Superclass::RealType                RealType;
  typedef typename Superclass::TransformType           TransformType;
  typedef typename Superclass::TransformPointer        TransformPointer;
  typedef typename Superclass::TransformParametersType TransformParametersType;
  typedef typename Superclass::TransformJacobianType   TransformJacobianType;
  typedef typename Superclass::GradientImageType       GradientImageType;
  typedef typename Superclass::GradientPixelType       GradientPixelType;
  typedef typename Superclass::InputPointType          InputPointType;
  typedef typename Superclass::OutputPointType         OutputPointType;

  typedef typename Superclass::MeasureType             MeasureType;
  typedef typename Superclass::DerivativeType          DerivativeType;
  typedef typename Superclass::FixedImageType          FixedImageType;
  typedef typename Superclass::MovingImageType         MovingImageType;
  typedef typename Superclass::FixedImageConstPointer  FixedImageConstPointer;
  typedef typename Superclass::MovingImageConstPointer MovingImageConstPointer;
  typedef typename Superclass::FixedImageRegionType    FixedImageRegionType;

  /** Computes the gradient image and assigns it to m_GradientImage */
  void ComputeGradient();

  /** Get the derivatives of the match measure. */
  void GetDerivative(const TransformParametersType &,
                     DerivativeType & derivative) const;

  /** Get the value of the metric at a particular parameter
   *  setting.  The metric value is given by 2*|A&B|/(|A|+|B|), where A
   *  is the moving image, B is the fixed image, & is intersection,
   *  and |.| indicates the area of the enclosed set.  If ComplementOn has
   *  been set, the metric value is 1.0-2*|A&B|/(|A|+|B|). */
  MeasureType GetValue(const TransformParametersType & parameters) const;

  /** Get both the value and derivative. This method internally calls the
    \c GetValue() and the \c GetDerivative() method. */
  void GetValueAndDerivative(const TransformParametersType & parameters,
                             MeasureType & Value, DerivativeType & Derivative) const;

  /** This method allows the user to set the foreground value.  The default
   *  value is 255. */
  itkSetMacro(ForegroundValue, RealType);
  itkGetConstMacro(ForegroundValue, RealType);

  /** Set/Get whether this metric returns 2*|A&B|/(|A|+|B|)
   * (ComplementOff, the default) or 1.0 - 2*|A&B|/(|A|+|B|)
   * (ComplementOn). When using an optimizer that minimizes
   * metric values use ComplementOn().  */
  itkSetMacro(Complement, bool);
  itkBooleanMacro(Complement);
  itkGetConstMacro(Complement, bool);

protected:
  KappaStatisticImageToImageMetric();
  virtual ~KappaStatisticImageToImageMetric() {}
  void PrintSelf(std::ostream & os, Indent indent) const;

private:
  KappaStatisticImageToImageMetric(const Self &); //purposely not implemented
  void operator=(const Self &);                   //purposely not implemented

  RealType m_ForegroundValue;
  bool     m_Complement;
};
} // end namespace itk

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

#endif