SignedEuclideanDistanceTransform

MacroModule

genre	Distance
author	MeVis Medical Solutions AG
package	MeVisLab/Standard
definition	SignedEuclideanDistanceTransform.def

Purpose

The SignedEuclideanDistanceTransform module provides a signed distance image defined by the distance to the foreground object surface. Positions inside of the object have negative distance and outside positions positive distances.

Internally the module uses either the fast computation with one EuclideanDistanceTransform module or two EuclideanDistanceTransform modules. This depends on the selected Distance Mode. The mode ForegroundVoxelCenter and ForegoundVoxelBorder2 always use one EuclideanDistanceTransform module whereas with ForegroundVoxelBorder mode two of this modules are used. Independent of the chosen mode, the result is always an object with negative values inside and positive values on the outside.

Windows

Default Panel

Parameter Fields

Field Index

Clear: Trigger

Dimension: Enum

Distance Mode: Enum

Max Value: Double

Min Value: Double

Update: Trigger

Visible Fields

Min Value

name: minValue, type: Double, default: 1

The minimum value of the foreground object.

Max Value

name: maxValue, type: Double, default: 1

The maximum value of the foreground object.

Update

name: update, type: Trigger

Updates the output volume.

Clear

name: clear, type: Trigger

Clears the output volume.

Distance Mode

name: distanceMode, type: Enum, default: ForegroundVoxelCenter

Defines the distance calculation mode.

Values:

Title	Name	Description
Center	ForegroundVoxelCenter	Distance is calculated from the center of the foreground object voxels. Foreground border voxels have a distance of 0 in the distance image. The border voxels are connected with a connectivity of 18.
Border	ForegroundVoxelBorder	Distance is calculated from the border of the foreground object voxels. Foreground border voxels have a negative distance of half a voxel in the distance image.
Border2	ForegroundVoxelBorder2	Distance is calculated from the border of the border foreground object voxels. Foreground border voxels have a distance of 0 in the distance image. The border voxels are connected with a connectivity of 18. This is similar to ForegroundVoxelCenter, but all distances other than zero are reduced by 0.5 towards zero. This is also faster than ForegroundVoxelBorder.

Dimension

name: dimension, type: Enum, default: 3D

Defines the dimensions considered for calculation of the Euclidean distance

Values:

Title	Name	Description
2d	2D	Euclidean distance is calculated in 2D.
3d	3D	Euclidean distance is calculated in 3D.