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/*=========================================================================
Program: Advanced Normalization Tools
Module: $RCSfile: itkContourDirectedMeanDistanceImageFilter.h,v $
Language: C++
Date: $Date: 2009-04-25 12:27:20 $
Version: $Revision: 1.7 $
Copyright (c) ConsortiumOfANTS. All rights reserved.
See accompanying COPYING.txt or
http://sourceforge.net/projects/advants/files/ANTS/ANTSCopyright.txt 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 __itkContourDirectedMeanDistanceImageFilter_h
#define __itkContourDirectedMeanDistanceImageFilter_h
#include "itkImageToImageFilter.h"
#include "itkNumericTraits.h"
#include "itkArray.h"
#include "itkImage.h"
namespace itk {
/** \class ContourDirectedMeanDistanceImageFilter
* \brief Computes the directed Mean distance between the boundaries of
* non-zero pixel regions of two images.
*
* ContourDirectedMeanDistanceImageFilter computes the distance between the set
* non-zero pixels of two images using the following formula:
* \f[ h(A,B) = \mathrm{mean}_{a \in A} \min_{b \in B} \| a - b\| \f]
* where \f$A\f$ and \f$B\f$ are respectively the set of non-zero pixels
* in the first and second input images. It identifies the point \f$ a \in A \f$
* that is farthest from any point of \f$B\f$ and measures the distance from \f$a\f$
* to the nearest neighbor in \f$B\f$. Note that this function is not
* is not symmetric and hence is not a true distance.
*
* In particular, this filter uses the SignedDanielssonDistanceMapImageFilter inside
* to compute distance map from all non-zero pixels in the second image. It
* then computes the mean distance (in pixels) within the boundary pixels of
* non-zero regions in the first image.
*
* Use MeanDistanceImageFilter to compute the full Mean distance.
*
* This filter requires the largest possible region of the first image and the
* same corresponding region in the second image. It behaves as filter with
* two input and one output. Thus it can be inserted in a pipeline with other
* filters. The filter passes the first input through unmodified.
*
* This filter is templated over the two input image type. It assume
* both image have the same number of dimensions.
*
* \sa SignedDanielssonDistanceMapImageFilter
* \sa MeanDistanceImageFilter
*
* \ingroup MultiThreaded
*
* \author Teo Popa, ISIS Center, Georgetown University
*
*/
template<class TInputImage1, class TInputImage2>
class ITK_EXPORT ContourDirectedMeanDistanceImageFilter :
public ImageToImageFilter<TInputImage1, TInputImage1>
{
public:
/** Standard Self typedef */
typedef ContourDirectedMeanDistanceImageFilter Self;
typedef ImageToImageFilter<TInputImage1,TInputImage1> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Runtime information support. */
itkTypeMacro(ContourDirectedMeanDistanceImageFilter, ImageToImageFilter);
/** Image related typedefs. */
typedef TInputImage1 InputImage1Type;
typedef TInputImage2 InputImage2Type;
typedef typename TInputImage1::Pointer InputImage1Pointer;
typedef typename TInputImage2::Pointer InputImage2Pointer;
typedef typename TInputImage1::ConstPointer InputImage1ConstPointer;
typedef typename TInputImage2::ConstPointer InputImage2ConstPointer;
typedef typename TInputImage1::RegionType RegionType;
typedef typename TInputImage1::SizeType SizeType;
typedef typename TInputImage1::IndexType IndexType;
typedef typename TInputImage1::PixelType InputImage1PixelType;
typedef typename TInputImage2::PixelType InputImage2PixelType;
/** Image related typedefs. */
itkStaticConstMacro(ImageDimension, unsigned int,
TInputImage1::ImageDimension);
/** Type to use form computations. */
typedef typename NumericTraits<InputImage1PixelType>::RealType RealType;
/** Set the first input. */
void SetInput1( const InputImage1Type * image )
{
this->SetInput( image );
}
/** Set the second input. */
void SetInput2( const InputImage2Type * image );
/** Get the first input. */
const InputImage1Type * GetInput1(void)
{
return this->GetInput();
}
/** Get the second input. */
const InputImage2Type * GetInput2(void);
/** Return the computed directed Mean distance. */
itkGetConstMacro(ContourDirectedMeanDistance,RealType);
#ifdef ITK_USE_CONCEPT_CHECKING
/** Begin concept checking */
itkConceptMacro(InputHasNumericTraitsCheck,
(Concept::HasNumericTraits<InputImage1PixelType>));
/** End concept checking */
#endif
protected:
ContourDirectedMeanDistanceImageFilter();
~ContourDirectedMeanDistanceImageFilter(){};
void PrintSelf(std::ostream& os, Indent indent) const;
/** Pass the input through unmodified. Do this by Grafting in the AllocateOutputs method. */
void AllocateOutputs();
/** Initialize some accumulators before the threads run. */
void BeforeThreadedGenerateData ();
/** Do final mean and variance computation from data accumulated in threads. */
void AfterThreadedGenerateData ();
/** Multi-thread version GenerateData. */
void ThreadedGenerateData (const RegionType&
outputRegionForThread,
int threadId);
// Override since the filter needs all the data for the algorithm
void GenerateInputRequestedRegion();
// Override since the filter produces all of its output
void EnlargeOutputRequestedRegion(DataObject *data);
private:
ContourDirectedMeanDistanceImageFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
typedef Image<RealType,itkGetStaticConstMacro(ImageDimension)> DistanceMapType;
typename DistanceMapType::Pointer m_DistanceMap;
Array<RealType> m_MeanDistance;
Array<int> m_Count;
RealType m_ContourDirectedMeanDistance;
}; // end of class
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkContourDirectedMeanDistanceImageFilter.txx"
#endif
#endif
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