Journal article

A gyrification analysis approach based on Laplace Beltrami eigenfunction level sets

Rosita Shishegar, Fabrizio Pizzagalli, Nellie Georgiou-Karistianis, Gary F Egan, Neda Jahanshad, Leigh A Johnston

NeuroImage | Elsevier | Published : 2021

Abstract

An accurate measure of the complexity of patterns of cortical folding or gyrification is necessary for understanding normal brain development and neurodevelopmental disorders. Conventional gyrification indices (GIs) are calculated based on surface curvature (curvature-based GI) or an outer hull surface of the cortex (outer surface-based GI). The latter is dependent on the definition of the outer hull surface and a corresponding function between surfaces. In the present study, we propose the Laplace Beltrami-based gyrification index (LB-GI). This is a new curvature-based local GI computed using the first three Laplace Beltrami eigenfunction level sets. As with outer surface-based GI methods, ..

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University of Melbourne Researchers