EM Fiber Clustering Module
For version 3.6.2 and beyond, please refer to DTI Fiber Clustering Module-Documentation-3.6.2. The new version has two new capabilities: Atlas-based seeding and multi-subject tract-based quantitative analysis.
Module Type & Category
Authors, Collaborators & Contact
- Mahnaz Maddah
- James Miller
- Contact: Mahnaz Maddah, mmaddah [at] alum.mit.edu
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.
Examples, Use Cases & Tutorials
Tutorial and test data can be downloaded from here:
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.
Notes from the Developer(s)
This module is based on the algorithms developped for quantitative analysis of white matter fiber tracts as a part of the author's PhD work: Mahnaz Maddah, Quantitative Analysis of Cerebral White Matter Anatomy from Diffusion MRI, Ph.D. Thesis CSAIL, MIT, September 2008.
On the Dashboard, these tests verify that the module is working on various platforms:
- Test EMClusteringTest.cxx
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Source code & documentation
Source code link
This work has been supported by NAC.