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Automatic and accurate parcellation of cortical surfaces into anatomically and functionally meaningful regions is of fundamental importance in brain mapping. In this paper, we propose a new method leveraging random forests and graph cuts methods to parcellate cortical surfaces into a set of gyral-based regions, using multiple surface atlases with manual labels by experts. Specifically, our method first takes advantage of random forests and auto-context methods to learn the optimal utilizationdoi:10.1109/isbi.2015.7163995 pmid:26405505 pmcid:PMC4578305 dblp:conf/isbi/MengLGS15 fatcat:vfs6aana45bghjiusevjx6gozi