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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 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
* \ingroup ITKLevelSets
*/
template< typename TInputImage,
typename TFeatureImage,
typename TOutputPixelType = float >
class ITK_TEMPLATE_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() ITK_OVERRIDE {}
LaplacianSegmentationLevelSetImageFilter();
virtual void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(LaplacianSegmentationLevelSetImageFilter);
typename LaplacianFunctionType::Pointer m_LaplacianFunction;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkLaplacianSegmentationLevelSetImageFilter.hxx"
#endif
#endif
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