Level Set-Based Segmentation Filters
[Model-Based Image Segmentation Filters]

Classes
class	AuxVarTypeDefault
	Level set auxiliary variables type information. AuxVarTypeDefault is a simple class that holds type information for auxiliary variables in some level set algorithms. This class is templated over the auxiliary variable data type, the number of auxiliary variables and the level set dimension. More...
class	CurvesLevelSetImageFilter
	Segments structures in images based on user supplied edge potential map. More...
class	ExtensionVelocitiesImageFilter
	Extend velocities smoothly from a particular level set. More...
class	FastMarchingExtensionImageFilter
	Extend auxiliary variables smoothly using Fast Marching. More...
class	FastMarchingImageFilter
	Solve an Eikonal equation using Fast Marching. More...
class	FiniteDifferenceImageFilter
class	GeodesicActiveContourLevelSetImageFilter
	Segments structures in images based on a user supplied edge potential map. More...
class	GeodesicActiveContourShapePriorLevelSetImageFilter
	Segments structures in an image based on a user supplied edge potential map and user supplied shape model. More...
class	IsoContourDistanceImageFilter
	Compute an approximate distance from an interpolated isocontour to the close grid points. More...
class	LevelSetNeighborhoodExtractor
	Locate pixels of a particular level set. More...
class	LevelSetNode
	Represent a node in a level set. More...
class	LevelSetTypeDefault
	Level set type information. More...
class	LevelSetVelocityNeighborhoodExtractor
	Locate pixels of a particular level set. More...
class	NarrowBandCurvesLevelSetImageFilter
	Segments structures in images based on user supplied edge potential map. More...
class	ReinitializeLevelSetImageFilter
	Reinitialize the level set to the signed distance function. More...
class	ShapeDetectionLevelSetImageFilter
	Segments structures in images based on a user supplied edge potential map. More...

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Detailed Description

These algorithms represent models implicitly using level-sets and update the models based on image features. Examples of these types of segmentation methods in ITK include: curvature flow-based filters, fast marching filters, and shape-detection filters.

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