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itkLaplacianSegmentationLevelSetImageFilter.h
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itkLaplacianSegmentationLevelSetImageFilter.h
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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkLaplacianSegmentationLevelSetImageFilter.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 __itkLaplacianSegmentationLevelSetImageFilter_h_
#define __itkLaplacianSegmentationLevelSetImageFilter_h_
#include "itkSegmentationLevelSetImageFilter.h"
#include "itkLaplacianSegmentationLevelSetFunction.h"
namespace itk {
/** \class LaplacianSegmentationLevelSetImageFilter
* \brief Segments structures in images based on a second derivative image features.
*
* \par IMPORTANT
* The SegmentationLevelSetImageFilter class and the
* LaplacianSegmentationLevelSetFunction class contain additional information necessary
* to the full understanding of how to use this filter.
*
* \par OVERVIEW
* This class is a level set method segmentation filter. It constructs a
* speed function which is zero at image edges as detected by a Laplacian
* filter. The evolving level set front will therefore tend to lock
* onto zero crossings in the image. The level set front moves fastest near
* edges.
*
* \par
* The Laplacian segmentation filter is intended primarily as a tool for
* refining existing segmentations. The initial isosurface (as given in the
* seed input image) should ideally be very close to the segmentation
* boundary of interest. The idea is that a rough segmentation can be
* refined by allowing the isosurface to deform slightly to achieve a better
* fit to the edge features of an image. One example of such an application
* is to refine the output of a hand segmented image.
*
* \par
* Because values in the Laplacian feature image will tend to be low except
* near edge features, this filter is not effective for segmenting large
* image regions from small seed surfaces.
*
*
* \par INPUTS
* This filter requires two inputs. The first input is a seed
* image. This seed image must contain an isosurface that you want to use as the
* seed for your segmentation. It can be a binary, graylevel, or floating
* point image. The only requirement is that it contain a closed isosurface
* that you will identify as the seed by setting the IsosurfaceValue parameter
* of the filter. For a binary image you will want to set your isosurface
* value halfway between your on and off values (i.e. for 0's and 1's, use an
* isosurface value of 0.5).
*
* \par
* The second input is the feature image. This is the image from which the
* speed function will be calculated. For most applications, this is the
* image that you want to segment. The desired isosurface in your seed image
* should lie within the region of your feature image that you are trying to
* segment.
*
* Note that this filter does no preprocessing of the feature image before
* thresholding. Because second derivative calculations are highly
* sensitive to noise, isotropic or anisotropic smoothing of the feature
* image can dramatically improve the results.
*
* \par
* See SegmentationLevelSetImageFilter for more information on Inputs.
*
* \par OUTPUTS
* The filter outputs a single, scalar, real-valued image.
* Positive *values in the output image are inside the segmentated region
* and negative *values in the image are outside of the inside region. The
* zero crossings of *the image correspond to the position of the level set
* front.
*
* \par
* See SparseFieldLevelSetImageFilter and
* SegmentationLevelSetImageFilter for more information.
*
* \par PARAMETERS
* This filter has no parameters other than those described in
* SegmentationLevelSetImageFilter.
*
* \sa SegmentationLevelSetImageFilter
* \sa LaplacianSegmentationLevelSetFunction,
* \sa SparseFieldLevelSetImageFilter */
template <class TInputImage,
class TFeatureImage,
class TOutputPixelType = float>
class ITK_EXPORT LaplacianSegmentationLevelSetImageFilter
: public SegmentationLevelSetImageFilter<TInputImage, TFeatureImage, TOutputPixelType>
{
public:
/** Standard class typedefs */
typedef LaplacianSegmentationLevelSetImageFilter Self;
typedef SegmentationLevelSetImageFilter<TInputImage, TFeatureImage, TOutputPixelType> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Inherited typedef from the superclass. */
typedef typename Superclass::ValueType ValueType;
typedef typename Superclass::OutputImageType OutputImageType;
typedef typename Superclass::FeatureImageType FeatureImageType;
/** Type of the segmentation function */
typedef LaplacianSegmentationLevelSetFunction<OutputImageType,
FeatureImageType> LaplacianFunctionType;
/** Run-time type information (and related methods). */
itkTypeMacro(LaplacianSegmentationLevelSetImageFilter, SegmentationLevelSetImageFilter);
/** Method for creation through the object factory */
itkNewMacro(Self);
protected:
~LaplacianSegmentationLevelSetImageFilter() {}
LaplacianSegmentationLevelSetImageFilter();
virtual void PrintSelf(std::ostream &os, Indent indent) const;
private:
LaplacianSegmentationLevelSetImageFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
typename LaplacianFunctionType::Pointer m_LaplacianFunction;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkLaplacianSegmentationLevelSetImageFilter.txx"
#endif
#endif