Tractography-driven groupwise multi-scale parcellation of the cortex
Parisot S, Arslan S, Passerat-Palmbach J, Wells WM, Rueckert D (2015)
Publication Type: Conference contribution
Publication year: 2015
Journal
Publisher: Springer Verlag
Book Volume: 9123
Pages Range: 600-612
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Isle of Skye, GBR
DOI: 10.1007/978-3-319-19992-4_47
Abstract
The analysis of the connectome of the human brain provides key insight into the brain’s organisation and function, and its evolution in disease or ageing. Parcellation of the cortical surface into distinct regions in terms of structural connectivity is an essential step that can enable such analysis. The estimation of a stable connectome across a population of healthy subjects requires the estimation of a groupwise parcellation that can capture the variability of the connectome across the population. This problem has solely been addressed in the literature via averaging of connectivity profiles or finding correspondences between individual parcellations a posteriori. In this paper, we propose a groupwise parcellation method of the cortex based on diffusion MR images (dMRI). We borrow ideas from the area of cosegmentation in computer vision and directly estimate a consistent parcellation across different subjects and scales through a spectral clustering approach. The parcellation is driven by the tractography connectivity profiles, and information between subjects and across scales. Promising qualitative and quantitative results on a sizeable data-set demonstrate the strong potential of the method.
Involved external institutions
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
Veterans Affairs Healthcare System Boston and Harvard Medical School
United States (USA) (US)
United Kingdom (GB)
Veterans Affairs Healthcare System Boston and Harvard Medical School
United States (USA) (US)
How to cite
APA:
Parisot, S., Arslan, S., Passerat-Palmbach, J., Wells, W.M., & Rueckert, D. (2015). Tractography-driven groupwise multi-scale parcellation of the cortex. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 600-612). Isle of Skye, GBR: Springer Verlag.
MLA:
Parisot, Sarah, et al. "Tractography-driven groupwise multi-scale parcellation of the cortex." Proceedings of the 24th International Conference on Information Processing in Medical Imaging, IPMI 2015, Isle of Skye, GBR Springer Verlag, 2015. 600-612.
BibTeX: Download