Segments structures in images based on a second derivative image features. More...

#include <itkLaplacianSegmentationLevelSetImageFilter.h>

Inheritance diagram for itk::LaplacianSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >:

Collaboration diagram for itk::LaplacianSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >:

List of all members.

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef Superclass::FeatureImageType	FeatureImageType
typedef LaplacianSegmentationLevelSetFunction < OutputImageType, FeatureImageType >	LaplacianFunctionType
typedef Superclass::OutputImageType	OutputImageType
typedef SmartPointer< Self >	Pointer
typedef LaplacianSegmentationLevelSetImageFilter	Self
typedef SegmentationLevelSetImageFilter < TInputImage, TFeatureImage, TOutputPixelType >	Superclass
typedef Superclass::ValueType	ValueType
Public Member Functions
virtual const char *	GetNameOfClass () const
Protected Member Functions
virtual void	PrintSelf (std::ostream &os, Indent indent) const
Private Member Functions
	LaplacianSegmentationLevelSetImageFilter (const Self &)
void	operator= (const Self &)
Private Attributes
LaplacianFunctionType::Pointer	m_LaplacianFunction
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
static Pointer	New ()
	~LaplacianSegmentationLevelSetImageFilter ()
	LaplacianSegmentationLevelSetImageFilter ()

Detailed Description

template<class TInputImage, class TFeatureImage, class TOutputPixelType = float>
class itk::LaplacianSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >

Segments structures in images based on a second derivative image features.

IMPORTANT: The SegmentationLevelSetImageFilter class and the LaplacianSegmentationLevelSetFunction class contain additional information necessary to the full understanding of how to use this filter.

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.

: 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.

: 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.

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).

: 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.

: See SegmentationLevelSetImageFilter for more information on Inputs.

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.

: See SparseFieldLevelSetImageFilter and SegmentationLevelSetImageFilter for more information.

PARAMETERS: This filter has no parameters other than those described in SegmentationLevelSetImageFilter.

See also:: SegmentationLevelSetImageFilter; LaplacianSegmentationLevelSetFunction,; SparseFieldLevelSetImageFilter

Definition at line 104 of file itkLaplacianSegmentationLevelSetImageFilter.h.