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.

GeoSP是一种用于皮层分区的并行方法，基于测地距离创建皮层网格的分区，考虑了回缩脑回和沟回的拓扑结构。该方法通过图表征网格并在并行模式下执行K-means聚类，此外还有两种使用模式。结果表明，该方法对于两种模式，不同数量的子分区均表现出同质子分区，且执行时间较短。与Desikan-Killiany和Destrieux图集相比，GeoSP分区的均匀性更好，并且跨受试者的结构连接再现性差异较小。

GeoSP: 基于测地距离的大脑皮层表面划分的并行方法