Multi-view graph matching of cortical landmarks

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Abstract

Human brain image alignment based on cortical folding pattern has long been an intriguing yet challenging research topic. Recently, a new gyral folding pattern, termed gyral hinge, was proposed and characterized by the conjunction of gyri from multiple directions. The uniqueness and importance of gyral hinges lie in their structural and functional importance and potential cross-subject correspondence, making them possible to be used as cortical landmarks. However, such an anatomical correspondence based on these new cortical landmarks is not fully studied and not related to structural connective similarity and functional coherence. Thus, we investigate whether the single use of structural connective or functional interactive diagrams, or the joint use of them could improve the alignment of these gyral hinges. Based on the pairwise graph matching method, we propose a multi-view framework in which all gyral hinges within a subject are taken as a system and its structural and functional connective networks are used as inputs. The results demonstrate that the joint use of structural and functional profiles outperforms those based on either of them and outperform those based on image registration methods.

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APA

Huang, Y., He, Z., Guo, L., Liu, T., & Zhang, T. (2019). Multi-view graph matching of cortical landmarks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11767 LNCS, pp. 84–92). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-32251-9_10

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