Structural Brain Mapping
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 cons
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Florida International University, Miami, Florida 33199, USA The Ohio State University, Columbus, Ohio 43210, USA
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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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Introduction
Brain mapping was introduced to map the genus zero 3D brain cortical surface (usually brain hemisphere) onto a unit sphere or a planar canonical domain (e.g., a unit disk, a rectangle domain), so that the convoluted and invisible cortical folds are flattened and the geometric details are fully exposed onto the canonical domain. A plausible category of methods is conformal mapping, which preserves angles (local shapes) and therefore is highly desired for brain morphometry study in neuroscience and medical imaging fields. It has been well studied in recent works using spherical harmonic mapping [1], Ricci curvature flow [2] and other methods [3]. Another commonly used category of methods is area-preserving brain mapping [4,5], computed based on optimal mass transportation theory. Brain anatomical landmarks including gyri and sulci curves are used to help shape registration and analysis applications. One method [2] is to slice the brain surface open along these curves, and map the new surface to a unit disk with circular holes or a hyperbolic polygon; the curves are mapped to circular holes or hyperbolic lines for generating intrinsic shape signatures. The other method [6] c Springer International Publishing Switzerland 2015 N. Navab et al. (Eds.): MICCAI 2015, Part III, LNCS 9351, pp. 760–767, 2015. DOI: 10.1007/978-3-319-24574-4_91
Structural Brain Mapping
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is to map the whole brain surface with interior curve straightening constraints based on holomorphic 1-form method, without changing surface
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