1 research outputs found
Cortical surface parcellation based on intra-subject white matter fiber clustering
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.Comment: 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, CONICYT PFCHA/ DOCTORADO
NACIONAL/2016-21160342, CONICYT FONDECYT 1190701, CONICYT PIA/Anillo de
Investigaci\'on en Ciencia y Tecnolog\'ia ACT172121 and CONICYT Basal Center
FB000