Joint generative model for fMRI/DWI and its application to population
Name
Golland_Joint generative.pdf
Size
764.71 KB
Format
Adobe PDF
Checksum (MD5)
000e7778952544fe6a0019dc1bb76124
Author(s)
Venkataraman, Archana
Rathi, Yogesh
Kubicki, Marek
Westin, Carl-Fredrik
Golland, Polina
Date Issued
September 2010
Journal
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010
Publisher
Springer Berlin / Heidelberg
Citation
Hutchison, David et al. “Joint Generative Model for fMRI/DWI and Its Application to Population Studies.” Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010. Ed. Tianzi Jiang et al. LNCS Vol. 6361. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. 191–199.
Version
Author's final manuscript
Abstract
We propose a novel probabilistic framework to merge information from DWI tractography and resting-state fMRI correlations. In particular, we model the interaction of latent anatomical and functional connectivity templates between brain regions and present an intuitive extension to population studies. We employ a mean-field approximation to fit the new model to the data. The resulting algorithm identifies differences in latent connectivity between the groups. We demonstrate our method on a study of normal controls and schizophrenia patients.
Description
Author Manuscript 2011 March 12. 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1007/978-3-642-15705-9_24
