Group-wise graph matching of cortical gyral hinges

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Abstract

Human brain image alignment has long been an intriguing research topic. The difficulty lies in the huge inter-individual variation. Also, it is not fully understood how structural similarity across subjects is related to functional correspondence. Recently, a gyral folding pattern, which is the conjunction of gyri from multiple directions and termed gyral hinge, was characterized. Gyral hinges have been demonstrated to have structural and functional importance and some of them were found to have cross-subject correspondences by manual labeling. However, there is no automatic method to estimate the cross-subject correspondences for whole-brain gyral hinges yet. To this end, we propose a novel group-wise graph matching framework, to which we feed structural connective matrices among gyral hinges from all subjects. The correspondence estimated by this framework is demonstrated by cross-subject consistency of both structural connective and functional profiles. Also, our results outperform the correspondences identified by pairwise graph matching and image-based registration methods.

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Zhang, T., Li, X., Zhao, L., Huang, Y., He, Z., Guo, L., & Liu, T. (2019). Group-wise graph matching of cortical gyral hinges. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11767 LNCS, pp. 75–83). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-32251-9_9

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