libinsighttoolkit3-dev 3.20.1-1 / usr / include / InsightToolkit / Algorithms / itkKappaStatisticImageToImageMetric.h

/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    itkKappaStatisticImageToImageMetric.h
  Language:  C++
  Date:      $Date$
  Version:   $Revision$

  Copyright (c) Insight Software Consortium. All rights reserved.
  See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.

     This software is distributed WITHOUT ANY WARRANTY; without even 
     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR 
     PURPOSE.  See the above copyright notices for more information.

=========================================================================*/
#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
 */
template < class TFixedImage, class TMovingImage > 
class ITK_EXPORT 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.txx"
#endif

#endif