Brain morphometry by distance measurement in a non-euclidean, curvilinear space

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Abstract

Inspired by the discussion in neurological research about the callosal fiber connections with respect to brain asymmetry we developed a technique that measures distances between brain hemispheres in a non-Euclidean, curvilinear space. The technique is a generic morphometric tool for measuring minimal distances within and across 3-D structures. We applied the technique for distances from the cortical gray/white matter boundary to the cross-section of the corpus callosum. The method uses a 3-D extension of the F*-algorithm. The algorithm uses a cost matrix determined by the image data. The resulting distances are mapped to the cortical surface and differences on the two hemispheres can be visually compared. Distances were also projected back to the corpus callosum to represent asymmetry by comparing left and right measurements. We can present results obtained by processing 11 3-D magnetic resonance data sets representing a normal control group.

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Styner, M., Coradi, T., & Gerig, G. (1999). Brain morphometry by distance measurement in a non-euclidean, curvilinear space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1613, pp. 364–369). Springer Verlag. https://doi.org/10.1007/3-540-48714-x_30

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