Documentation/4.3/Modules/LabelMapSmoothing

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Introduction and Acknowledgements

This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on NA-MIC can be obtained from the NA-MIC website. Author: FIRSTNAME LASTNAME, AFFILIATION Contributor1: FIRSTNAME LASTNAME, AFFILIATION Contributor2: FIRSTNAME LASTNAME, AFFILIATION Contact: FIRSTNAME LASTNAME, <email>john@doe.org</email>

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Module Description

This filter smoothes a binary label map. With a label map as input, this filter runs an anti-alising algorithm followed by a Gaussian smoothing algorithm. The output is a smoothed label map.

Use Cases

Use this when you have ragged segmentations in a volume, due perhaps to subject motion or inconsistent slice-by-slice manual editing.

Tutorials

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Panels and their use

Parameters:

• Label Selection Parameters: Parameters for selecting the label to smooth
  • Label to smooth: The label to smooth. All others will be ignored. If no label is selected by the user, the maximum label in the image is chosen by default.
• AntiAliasing Parameters: Parameters for the AntiAliasing algorithm
  • Number of Iterations: The number of iterations of the level set AntiAliasing algorithm
  • Maximum RMS Error: The maximum RMS error.
• Gaussian Smoothing Parameters: Parameters for Gaussian Smoothing
  • Sigma: The standard deviation of the Gaussian kernel
• IO: Input/output parameters
  • Input Volume: Input label map to smooth
  • Output Volume: Smoothed label map

Similar Modules

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References

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Information for Developers

[[Category:Documentation/4.3/Modules/

 Surface Models
 |LabelMapSmoothing]]