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 ForegoundVoxelCenterFast always uses one EuclideanDistanceTransform module whereas with ForegroundVoxelCenter or ForegroundVoxelBorder mode two of those modules are used. Independent of the chosen mode, the result is always an object with negative values inside and positive values on the outside. The results of ForegroundVoxelCenter and ForegroundVoxelCenterFast are equal.

Windows

Default Panel

../../../Modules/Macros/Distance/mhelp/Images/Screenshots/SignedEuclideanDistanceTransform._default.png

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.
CenterFast ForegroundVoxelCenterFast

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.

This uses a faster approach than ForegroundVoxelCenter.

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.