Abstract
Brain mapping plays an important role in neuroscience and medical imaging fields, which flattens the convoluted brain cortical surface and exposes the hidden geometry details onto a canonical domain. Existing methods such as conformal mappings didn’t consider the anatomical atlas network structure, and the anatomical landmarks, e.g., gyri curves, appear highly curvy on the canonical domains. Using such maps, it is difficult to recognize the connecting pattern and compare the atlases. In this work, we present a novel brain mapping method to efficiently visualize the convoluted and partially invisible cortical surface through a well-structured view, called the structural brain mapping. In computation, the brain atlas network (“node” - the junction of anatomical cortical regions, “edge” - the connecting curve between cortical regions) is first mapped to a planar straight line graph based on Tutte graph embedding, where all the edges are crossing-free and all the faces are convex polygons; the brain surface is then mapped to the convex shape domain based on harmonic map with linear constraints. Experiments on two brain MRI databases, including 250 scans with automatic atlases processed by FreeSurfer and 40 scans with manual atlases from LPBA40, demonstrate the efficiency and efficacy of the algorithm and the practicability for visualizing and comparing brain cortical anatomical structures.
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Razib, M., Lu, ZL., Zeng, W. (2015). Structural Brain Mapping. In: Navab, N., Hornegger, J., Wells, W., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science(), vol 9351. Springer, Cham. https://doi.org/10.1007/978-3-319-24574-4_91
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DOI: https://doi.org/10.1007/978-3-319-24574-4_91
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