GeoSP: A parallel method for a cortical surface parcellation based on geodesic distance

• URL: http://arxiv.org/abs/2103.14579v1
• Date: Fri, 26 Mar 2021 16:43:04 GMT
• Title: GeoSP: A parallel method for a cortical surface parcellation based on geodesic distance
• Authors: Narciso L\'opez-L\'opez, Andrea V\'azquez, Cyril Poupon, Jean-Fran\c{c}ois Mangin, Susana Ladra, and Pamela Guevara
• Abstract summary: GeoSP is a parallel method that creates a parcellation of the cortical mesh based on a geodesic distance. The proposed method will be available to the community to perform the evaluation of data-driven cortical parcellations.
• Score: 0.2955543753858105
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present GeoSP, a parallel method that creates a parcellation of the cortical mesh based on a geodesic distance, in order to consider gyri and sulci topology. The method represents the mesh with a graph and performs a K-means clustering in parallel. It has two modes of use, by default, it performs the geodesic cortical parcellation based on the boundaries of the anatomical parcels provided by the Desikan-Killiany atlas. The other mode performs the complete parcellation of the cortex. Results for both modes and with different values for the total number of sub-parcels show homogeneous sub-parcels. Furthermore, the execution time is 82 s for the whole cortex mode and 18 s for the Desikan-Killiany atlas subdivision, for a parcellation into 350 sub-parcels. The proposed method will be available to the community to perform the evaluation of data-driven cortical parcellations. As an example, we compared GeoSP parcellation with Desikan-Killiany and Destrieux atlases in 50 subjects, obtaining more homogeneous parcels for GeoSP and minor differences in structural connectivity reproducibility across subjects.

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