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vtkImageEuclideanDistance Class Reference

computes 3D Euclidean DT More...

#include <vtkImageEuclideanDistance.h>

Inheritance diagram for vtkImageEuclideanDistance:
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List of all members.

Public Types

typedef vtkImageDecomposeFilter Superclass

Public Member Functions

virtual int IsA (const char *type)
vtkImageEuclideanDistanceNewInstance () const
void PrintSelf (ostream &os, vtkIndent indent)
virtual int IterativeRequestData (vtkInformation *, vtkInformationVector **, vtkInformationVector *)
int SplitExtent (int splitExt[6], int startExt[6], int num, int total)
virtual void SetInitialize (int)
virtual int GetInitialize ()
virtual void InitializeOn ()
virtual void InitializeOff ()
virtual void SetConsiderAnisotropy (int)
virtual int GetConsiderAnisotropy ()
virtual void ConsiderAnisotropyOn ()
virtual void ConsiderAnisotropyOff ()
virtual void SetMaximumDistance (double)
virtual double GetMaximumDistance ()
virtual void SetAlgorithm (int)
virtual int GetAlgorithm ()
void SetAlgorithmToSaito ()
void SetAlgorithmToSaitoCached ()

Static Public Member Functions

static vtkImageEuclideanDistanceNew ()
static int IsTypeOf (const char *type)
static vtkImageEuclideanDistanceSafeDownCast (vtkObjectBase *o)

Protected Member Functions

virtual vtkObjectBaseNewInstanceInternal () const
 vtkImageEuclideanDistance ()
 ~vtkImageEuclideanDistance ()
virtual void AllocateOutputScalars (vtkImageData *outData, int outExt[6], vtkInformation *outInfo)
virtual int IterativeRequestInformation (vtkInformation *in, vtkInformation *out)
virtual int IterativeRequestUpdateExtent (vtkInformation *in, vtkInformation *out)

Protected Attributes

double MaximumDistance
int Initialize
int ConsiderAnisotropy
int Algorithm

Detailed Description

computes 3D Euclidean DT

vtkImageEuclideanDistance implements the Euclidean DT using Saito's algorithm. The distance map produced contains the square of the Euclidean distance values.

The algorithm has a o(n^(D+1)) complexity over nxnx...xn images in D dimensions. It is very efficient on relatively small images. Cuisenaire's algorithms should be used instead if n >> 500. These are not implemented yet.

For the special case of images where the slice-size is a multiple of 2^N with a large N (typically for 256x256 slices), Saito's algorithm encounters a lot of cache conflicts during the 3rd iteration which can slow it very significantly. In that case, one should use ::SetAlgorithmToSaitoCached() instead for better performance.

References:

T. Saito and J.I. Toriwaki. New algorithms for Euclidean distance transformations of an n-dimensional digitised picture with applications. Pattern Recognition, 27(11). pp. 1551--1565, 1994.

O. Cuisenaire. Distance Transformation: fast algorithms and applications to medical image processing. PhD Thesis, Universite catholique de Louvain, October 1999. http://ltswww.epfl.ch/~cuisenai/papers/oc_thesis.pdf

Tests:
vtkImageEuclideanDistance (Tests)

Definition at line 56 of file vtkImageEuclideanDistance.h.


Member Typedef Documentation

Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3.

Reimplemented from vtkImageDecomposeFilter.

Definition at line 60 of file vtkImageEuclideanDistance.h.


Constructor & Destructor Documentation

Definition at line 116 of file vtkImageEuclideanDistance.h.


Member Function Documentation

Create an object with Debug turned off, modified time initialized to zero, and reference counting on.

Reimplemented from vtkAlgorithm.

static int vtkImageEuclideanDistance::IsTypeOf ( const char *  type) [static]

Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3.

Reimplemented from vtkImageDecomposeFilter.

virtual int vtkImageEuclideanDistance::IsA ( const char *  type) [virtual]

Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3.

Reimplemented from vtkImageDecomposeFilter.

Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3.

Reimplemented from vtkImageDecomposeFilter.

virtual vtkObjectBase* vtkImageEuclideanDistance::NewInstanceInternal ( ) const [protected, virtual]

Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3.

Reimplemented from vtkImageDecomposeFilter.

Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3.

Reimplemented from vtkImageDecomposeFilter.

void vtkImageEuclideanDistance::PrintSelf ( ostream &  os,
vtkIndent  indent 
) [virtual]

Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3.

Reimplemented from vtkImageDecomposeFilter.

int vtkImageEuclideanDistance::SplitExtent ( int  splitExt[6],
int  startExt[6],
int  num,
int  total 
) [virtual]

Used internally for streaming and threads. Splits output update extent into num pieces. This method needs to be called num times. Results must not overlap for consistent starting extent. Subclass can override this method. This method returns the number of peices resulting from a successful split. This can be from 1 to "total". If 1 is returned, the extent cannot be split.

Reimplemented from vtkThreadedImageAlgorithm.

virtual void vtkImageEuclideanDistance::SetInitialize ( int  ) [virtual]

Used to set all non-zero voxels to MaximumDistance before starting the distance transformation. Setting Initialize off keeps the current value in the input image as starting point. This allows to superimpose several distance maps.

Used to set all non-zero voxels to MaximumDistance before starting the distance transformation. Setting Initialize off keeps the current value in the input image as starting point. This allows to superimpose several distance maps.

virtual void vtkImageEuclideanDistance::InitializeOn ( ) [virtual]

Used to set all non-zero voxels to MaximumDistance before starting the distance transformation. Setting Initialize off keeps the current value in the input image as starting point. This allows to superimpose several distance maps.

virtual void vtkImageEuclideanDistance::InitializeOff ( ) [virtual]

Used to set all non-zero voxels to MaximumDistance before starting the distance transformation. Setting Initialize off keeps the current value in the input image as starting point. This allows to superimpose several distance maps.

Used to define whether Spacing should be used in the computation of the distances

Used to define whether Spacing should be used in the computation of the distances

Used to define whether Spacing should be used in the computation of the distances

Used to define whether Spacing should be used in the computation of the distances

Any distance bigger than this->MaximumDistance will not ne computed but set to this->MaximumDistance instead.

Any distance bigger than this->MaximumDistance will not ne computed but set to this->MaximumDistance instead.

virtual void vtkImageEuclideanDistance::SetAlgorithm ( int  ) [virtual]

Selects a Euclidean DT algorithm. 1. Saito 2. Saito-cached More algorithms will be added later on.

Selects a Euclidean DT algorithm. 1. Saito 2. Saito-cached More algorithms will be added later on.

Selects a Euclidean DT algorithm. 1. Saito 2. Saito-cached More algorithms will be added later on.

Definition at line 104 of file vtkImageEuclideanDistance.h.

Selects a Euclidean DT algorithm. 1. Saito 2. Saito-cached More algorithms will be added later on.

Definition at line 106 of file vtkImageEuclideanDistance.h.

Reimplemented from vtkImageIterateFilter.

virtual void vtkImageEuclideanDistance::AllocateOutputScalars ( vtkImageData outData,
int  outExt[6],
vtkInformation outInfo 
) [protected, virtual]

Reimplemented from vtkImageIterateFilter.

Reimplemented from vtkImageIterateFilter.


Member Data Documentation

Definition at line 118 of file vtkImageEuclideanDistance.h.

Definition at line 119 of file vtkImageEuclideanDistance.h.

Definition at line 120 of file vtkImageEuclideanDistance.h.

Definition at line 121 of file vtkImageEuclideanDistance.h.


The documentation for this class was generated from the following file: