AHM 2010 Tutorial Contest - EM Fiber Clustering
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EM Fiber Clustering Module
Contents
General Information
Authors, Collaborators & Contact
- Mahnaz Maddah
- James Miller
- Contact: Mahnaz Maddah, maddah@ge.com
Module Description
This module clusters a set of input trajectories into a number of bundles, generates arc length parameterization by establishing the point correspondences and reports diffusion parameters along the bundles as well as the membership probability of each trajectory in each cluster. The module requires specification of seed trajectories (or initial centerlines) as representatives of the desired bundles.
Usage
Examples, Use Cases & Tutorials
Fiber Clustering Tutorial Slides
Test data can be downloaded from here:
http://www.nitrc.org/projects/quantitativedti/
Quick Tour of Features and Use
Here is a list of the panels in the module:
- IO panel:
Trajectories Input trajectories to be clustered. Output Clusters Clustered trajecories labeled by their cluster ID. Initial Centers [optional] Initial center(s). Note that intial centers need to be provided by passing either a set of trajectories here or a fiducial list. Fiducials to Pick Initial Centers [optional] A fiducial list to generate initial center(s). For each fiducial in the list the closest trajectory in the input is selected as the initial center. Output Initial Centers [Optional] Selected initial cluster centers. Output Final Centers [Optional] Final cluster centers, colored by the mean FA value along the bundle if "Perform Quantitative Analysis" is flaged . Perform Quantitative Analysis Flag that needs to be marked if quantitative analysis is desired to be done. Output Directory A directory needs to be specified if performing quantitative analysis. File Prefix Name Prefix of the output files generated through tract-oriented analysis. Description of generated CSV files by EM Clustering Module
- Clustering Parameters:
Compactness of Fiber Bundles Parameter between 1 and 5 that specifies the extent of similarity between the trajectories of each cluster. Increase the value for more compact bundles.
- Advanced Parameters:
Space Resolution Space resolution for distance map calculation. Iterations Maximum number of EM iterations. Maximum Distance Maximum distance in mm specifies an upper threshold on the distance of points that can contribute to new center formation.