GeoSP: A parallel method for a cortical surface parcellation based on geodesic distance
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.
Cite
@article{arxiv.2103.14579,
title = {GeoSP: A parallel method for a cortical surface parcellation based on geodesic distance},
author = {Narciso López-López and Andrea Vázquez and Cyril Poupon and Jean-François Mangin and Susana Ladra and Pamela Guevara},
journal= {arXiv preprint arXiv:2103.14579},
year = {2021}
}
Comments
This research has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Actions H2020-MSCA-RISE-2015 BIRDS GA No. 690941, ANID PFCHA/DOCTORADO NACIONAL/2016-21160342, ANID FONDECYT 1190701, ANID PIA/Anillo de Investigaci\'on en Ciencia y Tecnolog\'ia ACT172121, and ANID Basal Project FB0008