Group-Wise Cortical Surface Parcellation Based on Inter-Subject Fiber Clustering

• Published in: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2021; pp. 2655 - 2659
• Main Authors: Vergara, Christopher, Silva, Felipe, Huerta, Isaias, Lopez-Lopez, Narciso, Vazquez, Andrea, Houenou, Josselin, Poupon, Cyril, Mangin, Jean-Francois, Hernandez, Cecilia, Guevara, Pamela
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.11.2021
• Subjects: Algorithms; Biology; Brain; Brain modeling; Cerebral Cortex; Cluster Analysis; Clustering algorithms; Humans; Optical fiber testing; Reproducibility of Results
• ISSN: 2694-0604
• DOI: 10.1109/EMBC46164.2021.9631099

We present an automatic algorithm for the group-wise parcellation of the cortical surface. The method is based on the structural connectivity obtained from representative brain fiber clusters, calculated via an inter-subject clustering scheme. Preliminary regions were defined from cluster-cortical mesh intersection points. The final parcellation was obtained using parcel probability maps to model and integrate the connectivity information of all subjects, and graphs to represent the overlap between parcels. Two inter-subject clustering schemes were tested, generating a total of 171 and 109 parcels, respectively. The resulting parcels were quantitatively compared with three state-of-the-art atlases. The best parcellation returned 69 parcels with a Dice similarity coefficient greater than 0.5. To the best of our knowledge, this is the first diffusion-based cortex parcellation method based on whole-brain inter-subject fiber clustering.