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Erschienen in:
2019 | OriginalPaper | Buchkapitel
Conformal Welding for Brain-Intelligence Analysis
verfasst von : Liqun Yang, Muhammad Razib, Kenia Chang He, Tianren Yang, Zhong-Lin Lu, Xianfeng Gu, Wei Zeng
Erschienen in: Advances in Visual Computing
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Abstract
In this work, we present a geometric method to explore the relationship between brain anatomical structure and human intelligence based on conformal welding theory. We first generate the anatomical atlas on the structural MRI data; then, compute the signature for each cortical region by welding the conformal maps of the region and its complement domain along the common boundary, and combine all the region signature as that for the whole brain; and finally, use the signatures for shape visualization and classification using the learning methods. The signature is global, intrinsic to surface and curve geometry, and invariant to conformal transformations; and the computation is efficient through solving sparse linear systems. Experiments on real data set with 243 subjects demonstrate the efficacy of the proposed method and concluded that the conformal welding signature of cortical surface can classify human intelligence with a competitive accuracy rate compared with traditional features.