Joint generative model for fMRI/DWI and its application to population
Author(s)Venkataraman, Archana; Rathi, Yogesh; Kubicki, Marek; Westin, Carl-Fredrik; Golland, Polina
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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.
Author Manuscript 2011 March 12. 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010
Springer Berlin / Heidelberg
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.
Author's final manuscript