  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.
