Multi-level parcellation of the cerebral cortex using resting-state fMRI
Arslan S, Rueckert D (2015)
Publication Type: Conference contribution
Publication year: 2015
Journal
Publisher: Springer Verlag
Book Volume: 9351
Pages Range: 47-54
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Munich, DEU
ISBN: 9783319245737
DOI: 10.1007/978-3-319-24574-4_6
Abstract
Cortical parcellation is one of the core steps for identifying the functional architecture of the human brain. Despite the increasing number of attempts at developing parcellation algorithms using resting-state fMRI, there still remain challenges to be overcome, such as generating reproducible parcellations at both single-subject and group levels, while sub-dividing the cortex into functionally homogeneous parcels. To address these challenges, we propose a three-layer parcellation framework which deploys a different clustering strategy at each layer. Initially, the cortical vertices are clustered into a relatively large number of super-vertices, which constitutes a high-level abstraction of the rs-fMRI data. These supervertices are combined into a tree of hierarchical clusters to generate individual subject parcellations, which are, in turn, used to compute a groupwise parcellation in order to represent the whole population. Using data collected as part of the Human Connectome Project from 100 healthy subjects, we show that our algorithm segregates the cortex into distinctive parcels at different resolutions with high reproducibility and functional homogeneity at both single-subject and group levels, therefore can be reliably used for network analysis.
Involved external institutions
United Kingdom (GB)How to cite
APA:
Arslan, S., & Rueckert, D. (2015). Multi-level parcellation of the cerebral cortex using resting-state fMRI. In Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 47-54). Munich, DEU: Springer Verlag.
MLA:
Arslan, Salim, and Daniel Rueckert. "Multi-level parcellation of the cerebral cortex using resting-state fMRI." Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, Munich, DEU Ed. Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells, Springer Verlag, 2015. 47-54.
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