Group-Representative Functional Network Estimation from Multi-Subject fMRI Data via MRF-based Image Segmentation

29 Aug 2018 Aditi Iyer Bingjing Tang Vinayak Rao Nan Kong

We propose a novel two-phase approach to functional network estimation of multi-subject functional Magnetic Resonance Imaging (fMRI) data, which applies model-based image segmentation to determine a group-representative connectivity map. In our approach, we first improve clustering-based Independent Component Analysis (ICA) to generate maps of components occurring consistently across subjects, and then estimate the group-representative map through MAP-MRF (Maximum a priori - Markov random field) labeling... (read more)

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