학술논문

Cortical surface parcellation based on intra-subject white matter fiber clustering
Document Type
Conference
Source
2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), 2019 IEEE CHILEAN Conference on. :1-6 Nov, 2019
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Parcellation
clustering
white matter
connectivity
fibers
tractography
Language
Abstract
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) through-out 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 sub-parcels per hemisphere and complying with these connectivity measures.