FuzzyCluster¶

MLModule¶

genre	`Fuzzy`
status	`work-in-progress`
authors	`Michael Schwier`, `Sarah Behrens`
package	`MeVisLab/Standard`
dll	`MLFuzzy`
definition	MLFuzzy.def
see also	`IntervalThresh`, `FuzzyConnectDistance`
keywords	`fuzzy`, `cluster`, `fcm`, `cmeans`, `segmentation`, `classification`

Purpose¶

The module FuzzyCluster implements a fuzzy c-means algorithm that classifies an image into different clusters depending on the gray values.

Image voxels get a membership value ranging from 0 to 1 for each cluster. This permits for example to segment regions of the image by choosing clusters and membership thresholds.

Usage¶

Choose a number of classes you want the image to be classified into. Press the Calculate Cluster button. Since the calculation can be quite time-consuming, it is only started on demand and even then only if essential fields (like Fuzziness, Epsilon, etc.) were changed.

output1 always shows all clusters, with voxels being assigned to the clusters in which they have the highest membership (this is what you usually want). To be able to see something at output0 you also have to provide one or more valid markers at the inputMarkersVol input. After changing the markers you will need to press Calculate Cluster again, to see the clusters corresponding to the marked voxels. By adjusting the Membership Threshold you can define how high the membership of a voxel in relation to the chosen clusters have to be to be included in the output0 image.

It is highly recommended to use only images of an integer type (int, uint, etc.) as input!

The calculation time is significantly higher for float images, and big non-integer images the module cannot even handle.

Details¶

For details about the algorithm, read this.

Windows¶

Default Panel¶

../../../Modules/ML/MLFuzzy/mhelp/Images/Screenshots/FuzzyCluster._default.png

Input Fields¶

input0¶

name: input0, type: Image¶: The scalar input image.

inputMarkersVol¶

name: inputMarkersVol, type: MLBase¶: XMarkerList for selecting a specific cluster for output0.

Output Fields¶

output0¶

name: output0, type: Image¶

Output image showing the selected clusters.

The background voxels have value 0, the cluster voxels maximum image value.

output1¶

name: output1, type: Image¶

Output image showing all clusters.

The gray value of a voxel represents the index of the cluster it most belongs to.

Parameter Fields¶

Field Index¶

`acceptedMarkerType`: `Integer`	`Max membership difference`: `Double`	`Use gray value limit`: `Bool`
`Calculate Cluster`: `Trigger`	`maxSize`: `Integer`	`Value of Center`: `Double`
`Cluster Index`: `Integer`	`Membership Threshold`: `Double`	`weight`: `Double`
`Epsilon`: `Double`	`noSeeds`: `Integer`
`forceFullFCM`: `Bool`	`Number of Classes`: `Integer`
`Fuzziness`: `Double`	`objects`: `Integer`
`Iteration Limit`: `Integer`	`Performed Iterations`: `Integer`
`Lower gray value limit`: `Double`	`Upper gray value limit`: `Double`

Visible Fields¶

Number of Classes¶

name: classes, type: Integer, default: 3¶: Sets the number of clusters the image will be clustered into.

Max membership difference¶

name: calcCounter, type: Double, default: 0¶: Shows the value difference between the current and the previous calculation.

Epsilon¶

name: epsilon, type: Double, default: 0.3, minimum: 0, maximum: 1¶

Sets the stopping condition for the fuzzy c-mean iteration.

As long as the difference between the current and the previous iteration is greater than Epsilon, the iteration will continue.

Membership Threshold¶

name: threshold, type: Double, default: 0.5, minimum: 0, maximum: 1¶

Sets a threshold to include more cluster voxels to the selected cluster in output0.

Voxels with a difference to the selected cluster voxels within this threshold are added to the selected cluster.

Fuzziness¶

name: fuzziness, type: Double, default: 2, minimum: 1, maximum: 5¶: Sets the fuzzyness parameter.

Calculate Cluster¶

name: cluster, type: Trigger¶: If pressed, the module computes the output anew.

Use gray value limit¶

name: useGrayValueLimit, type: Bool, default: FALSE¶: If checked, the module only works on voxels with a value within Lower gray value limit and Upper gray value limit.

Lower gray value limit¶

name: lowerGrayValueLimit, type: Double, default: 0¶: Sets the lower gray value limit for cluster computation.

Upper gray value limit¶

name: upperGrayValueLimit, type: Double, default: 4095¶: Sets the upper gray value limit for cluster computation.

Cluster Index¶

name: clusterIndex, type: Integer, default: 0¶: Sets the index of the cluster about which information should be displayed.

Value of Center¶

name: clusterCenterGray, type: Double, default: 0¶: Shows the gray value of the center of the cluster selected with Cluster Index.

Iteration Limit¶

name: iterationLimit, type: Integer, default: 1000¶

Sets the maximum amount of iterations that are performed in the Fuzzy-C-Means calculation.

This is needed for cases where the fuzzy clustering does not converge.

A value of 0 means no limit.

Performed Iterations¶

name: performedIterations, type: Integer, default: 0¶

Shows the number of performed iterations.

If this field shows the same number as Iteration Limit, the fuzzy clustering probably did not converge.

Hidden Fields¶

noSeeds¶

name: noSeeds, type: Integer, default: 0¶

acceptedMarkerType¶

name: acceptedMarkerType, type: Integer, default: -1¶

maxSize¶

name: maxSize, type: Integer, default: 0¶

objects¶

name: objects, type: Integer, default: 4¶

weight¶

name: weight, type: Double, default: 1¶

forceFullFCM¶

name: forceFullFCM, type: Bool, default: FALSE¶

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