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/*=========================================================================
*
* 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 itkConfidenceConnectedImageFilter_h
#define itkConfidenceConnectedImageFilter_h
#include "itkImage.h"
#include "itkImageToImageFilter.h"
namespace itk
{
/** \class ConfidenceConnectedImageFilter
* \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 recalculated 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
* \ingroup ITKRegionGrowing
*
* \wiki
* \wikiexample{ImageSegmentation/ConfidenceConnectedImageFilter,Segment pixels with similar statistics using connectivity}
* \endwiki
*/
template< typename TInputImage, typename TOutputImage >
class ITK_TEMPLATE_EXPORT ConfidenceConnectedImageFilter:
public ImageToImageFilter< TInputImage, TOutputImage >
{
public:
/** Standard class typedefs. */
typedef ConfidenceConnectedImageFilter 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(ConfidenceConnectedImageFilter,
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 typename NumericTraits<
InputImagePixelType >::RealType InputRealType;
void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
/** Set seed point. This method is deprecated, please use AddSeed() */
void SetSeed(const IndexType & seed);
/** Clear all the seeds. */
void ClearSeeds();
/** Add seed point. */
void AddSeed(const IndexType & seed);
/** 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);
itkGetConstMacro(Multiplier, double);
/** Set/Get the number of iterations */
itkSetMacro(NumberOfIterations, unsigned int);
itkGetConstMacro(NumberOfIterations, unsigned int);
/** Set/Get value to replace thresholded pixels */
itkSetMacro(ReplaceValue, OutputImagePixelType);
itkGetConstMacro(ReplaceValue, OutputImagePixelType);
/** Get/Set the radius of the neighborhood over which the
statistics are evaluated */
itkSetMacro(InitialNeighborhoodRadius, unsigned int);
itkGetConstReferenceMacro(InitialNeighborhoodRadius, unsigned int);
/** Method to get access to the mean of the pixels accepted in the output
* region. This method should only be invoked after the filter has been
* executed using the Update() method. */
itkGetConstReferenceMacro(Mean, InputRealType);
/** Method to get access to the variance of the pixels accepted in the output
* region. This method should only be invoked after the filter has been
* executed using the Update() method. */
itkGetConstReferenceMacro(Variance, InputRealType);
/** Method to access seed container */
virtual const SeedsContainerType &GetSeeds() const;
#ifdef ITK_USE_CONCEPT_CHECKING
// Begin concept checking
itkConceptMacro( InputHasNumericTraitsCheck,
( Concept::HasNumericTraits< InputImagePixelType > ) );
itkConceptMacro( OutputHasNumericTraitsCheck,
( Concept::HasNumericTraits< OutputImagePixelType > ) );
// End concept checking
#endif
protected:
ConfidenceConnectedImageFilter();
~ConfidenceConnectedImageFilter() ITK_OVERRIDE {}
// Override since the filter needs all the data for the algorithm
void GenerateInputRequestedRegion() ITK_OVERRIDE;
// Override since the filter produces the entire dataset
void EnlargeOutputRequestedRegion(DataObject *output) ITK_OVERRIDE;
void GenerateData() ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(ConfidenceConnectedImageFilter);
SeedsContainerType m_Seeds;
double m_Multiplier;
unsigned int m_NumberOfIterations;
OutputImagePixelType m_ReplaceValue;
unsigned int m_InitialNeighborhoodRadius;
InputRealType m_Mean;
InputRealType m_Variance;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkConfidenceConnectedImageFilter.hxx"
#endif
#endif
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