We present a hybrid method that performs the complete parcellation of the cerebral cortex of an individual, based on the connectivity information of the white matter fibers from a whole-brain tractography dataset. The method consists of five steps, first intra-subject clustering is performed on the brain tractography. The fibers that make up each cluster are then intersected with the cortical mesh and then filtered to discard outliers. In addition, the method resolves the overlapping between the different intersection regions (sub-parcels) throughout the cortex efficiently. Finally, a post-processing is done to achieve more uniform sub-parcels. The output is the complete labeling of cortical mesh vertices, representing the different cortex sub-parcels, with strong connections to other sub-parcels. We evaluated our method with measures of brain connectivity such as functional segregation (clustering coefficient), functional integration (characteristic path length) and small-world. Results in five subjects from ARCHI database show a good individual cortical parcellation for each one, composed of about 200 subparcels per hemisphere and complying with these connectivity measures.

本文提出了一种基于脑白质纤维束连接信息对个体大脑皮层进行完整分区的混合方法，分为五个步骤，最终输出不同皮层的子区分标签。在功能分化、功能整合和小世界等方面，经过测试得出其效果良好。

基于个体白质纤维聚类的大脑皮层表面划分