Author: Mert R Sabuncu, © 2012-2013 email: firstname.lastname@example.org
A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology (MIT)
This is a Matlab implementation of the Relevance Voxel Machine, a Bayesian image-based multivariate pattern recognition/prediction algorithm.
For details on the methods, please refer to the following paper:
[Sabuncu, M., and Koen Van Leemput. “The Relevance Voxel Machine (RVoxM): A Self-tuning Bayesian Model for Informative Image-based Prediction.” (2012), vol. 31, no. 2, pp. 2290 – 2306 . [pdf]
CURRENT VERSION DOWNLOAD: Click here!
CURRENT VERSION NOTES: This is a beta version of the software. Inevitably, there are going to be bugs/errors in the code. I will try my best to fix them as I become aware of them. Updates will be posted as code fixes become available. Please email: email@example.com if you notice any bugs in the code or if you have any problems.
(1) If you don’t have FreeSurfer installed on your machine, download and install the latest version from here.
(2) Launch Matlab in the RVoxM directory, from the command line and after running the FreeSurfer setup script (which sets the FREESURFER_HOME variable)
(3) Setup mex, if this is the first time you’re using mex. (For help: http://www.mathworks.com/support/tech-notes/1600/1605.html)
(4) Run RVoxM_setup in Matlab.
(5) Try the two demo scripts: surface_demo_script (which handles FreeSurfer surface files) and volume_demo_script (which handles 3D volumes).
For questions/remarks/feedback/bugs: email firstname.lastname@example.org