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.
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 this when you have ragged segmentations in a volume, due perhaps to subject motion or inconsistent slice-by-slice manual editing.
Panels and their use
- Label Selection Parameters: Parameters for selecting the label to smooth
- Label to smooth (labelToSmooth): 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 (numberOfIterations): The number of iterations of the level set AntiAliasing algorithm
- Maximum RMS Error (maxRMSError): The maximum RMS error.
- Gaussian Smoothing Parameters: Parameters for Gaussian Smoothing
- Sigma (gaussianSigma): The standard deviation of the Gaussian kernel
- IO: Input/output parameters
- Input Volume (inputVolume): Input label map to smooth
- Output Volume (outputVolume): Smoothed label map
Information for Developers
|Section under construction.|
Surface Models |LabelMapSmoothing]]