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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkVectorConfidenceConnectedImageFilter.h,v $
Language: C++
Date: $Date: 2006-04-03 15:07:52 $
Version: $Revision: 1.4 $
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 __itkVectorConfidenceConnectedImageFilter_h
#define __itkVectorConfidenceConnectedImageFilter_h
#include "itkImage.h"
#include "itkImageToImageFilter.h"
#include "itkMahalanobisDistanceThresholdImageFunction.h"
namespace itk{
/** /class VectorConfidenceConnectedImageFilter
* /brief Segment pixels with similar statistics using connectivity
*
* This filter extracts a connected set of pixels whose pixel
* intensities are consistent with the pixel statistics of a seed
* point. The mean and variance across a neighborhood (8-connected,
* 26-connected, etc.) are calculated for a seed point. Then
* pixels connected to this seed point whose values are within
* the confidence interval for the seed point are grouped. The
* width of the confidence interval is controlled by the "Multiplier"
* variable (the confidence interval is the mean plus or minus
* the "Multiplier" times the standard deviation). If the intensity
* variations across a segment were gaussian, a "Multiplier" setting
* of 2.5 would define a confidence interval wide enough to capture
* 99% of samples in the segment.
*
* After this initial segmentation is calculated, the mean and
* variance are re-calculated. All the pixels in the previous
* segmentation are used to calculate the mean the standard deviation
* (as opposed to using the pixels in the neighborhood of the seed
* point). The segmentation is then recalculted using these refined
* estimates for the mean and variance of the pixel values. This
* process is repeated for the specified number of iterations.
* Setting the "NumberOfIterations" to zero stops the algorithm
* after the initial segmentation from the seed point.
*
* NOTE: the lower and upper threshold are restricted to lie within the
* valid numeric limits of the input data pixel type. Also, the limits
* may be adjusted to contain the seed point's intensity.
* \ingroup RegionGrowingSegmentation
*/
template <class TInputImage, class TOutputImage>
class ITK_EXPORT VectorConfidenceConnectedImageFilter:
public ImageToImageFilter<TInputImage,TOutputImage>
{
public:
/** Standard class typedefs. */
typedef VectorConfidenceConnectedImageFilter Self;
typedef ImageToImageFilter<TInputImage,TOutputImage> 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(VectorConfidenceConnectedImageFilter,
ImageToImageFilter);
typedef TInputImage InputImageType;
typedef typename InputImageType::Pointer InputImagePointer;
typedef typename InputImageType::RegionType InputImageRegionType;
typedef typename InputImageType::PixelType InputImagePixelType;
typedef typename InputImageType::IndexType IndexType;
typedef typename InputImageType::SizeType SizeType;
typedef TOutputImage OutputImageType;
typedef typename OutputImageType::Pointer OutputImagePointer;
typedef typename OutputImageType::RegionType OutputImageRegionType;
typedef typename OutputImageType::PixelType OutputImagePixelType;
typedef std::vector< IndexType > SeedsContainerType;
typedef MahalanobisDistanceThresholdImageFunction<
InputImageType >
DistanceThresholdFunctionType;
typedef typename DistanceThresholdFunctionType::CovarianceMatrixType CovarianceMatrixType;
typedef typename DistanceThresholdFunctionType::MeanVectorType MeanVectorType;
typedef typename DistanceThresholdFunctionType::Pointer DistanceThresholdFunctionPointer;
void PrintSelf ( std::ostream& os, Indent indent ) const;
/** Set seed point. This method is deprecated, please use AddSeed() */
void SetSeed(const IndexType & seed)
{
m_Seeds.clear();
this->AddSeed( seed );
};
/** Add seed point. */
void AddSeed(const IndexType & seed)
{
m_Seeds.push_back( seed );
this->Modified();
};
/** Set/Get the multiplier to define the confidence interval. Multiplier
* can be anything greater than zero. A typical value is 2.5 */
itkSetMacro(Multiplier, double);
itkGetMacro(Multiplier, double);
/** Set/Get the number of iterations */
itkSetMacro(NumberOfIterations, unsigned int);
itkGetMacro(NumberOfIterations, unsigned int);
/** Set/Get value to replace thresholded pixels */
itkSetMacro(ReplaceValue, OutputImagePixelType);
itkGetMacro(ReplaceValue, OutputImagePixelType);
/** Get/Set the radius of the neighborhood over which the
statistics are evaluated */
itkSetMacro( InitialNeighborhoodRadius, unsigned int );
itkGetConstReferenceMacro( InitialNeighborhoodRadius, unsigned int );
/** Get the Mean Vector computed during the segmentation */
const MeanVectorType & GetMean() const;
/** Get the Covariance matrix computed during the segmentation */
const CovarianceMatrixType & GetCovariance() const;
#ifdef ITK_USE_CONCEPT_CHECKING
/** Begin concept checking */
itkConceptMacro(OutputEqualityComparableCheck,
(Concept::EqualityComparable<OutputImagePixelType>));
itkConceptMacro(InputHasNumericTraitsCheck,
(Concept::HasNumericTraits<typename InputImagePixelType::ValueType>));
itkConceptMacro(OutputOStreamWritableCheck,
(Concept::OStreamWritable<OutputImagePixelType>));
/** End concept checking */
#endif
protected:
VectorConfidenceConnectedImageFilter();
// Override since the filter needs all the data for the algorithm
void GenerateInputRequestedRegion();
// Override since the filter produces the entire dataset
void EnlargeOutputRequestedRegion(DataObject *output);
void GenerateData();
private:
VectorConfidenceConnectedImageFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
SeedsContainerType m_Seeds;
double m_Multiplier;
unsigned int m_NumberOfIterations;
OutputImagePixelType m_ReplaceValue;
unsigned int m_InitialNeighborhoodRadius;
DistanceThresholdFunctionPointer m_ThresholdFunction;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkVectorConfidenceConnectedImageFilter.txx"
#endif
#endif
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