Abstract
We present a framework for registering cortical surfaces based on tractography-informed structural connectivity. We define connectivity as a continuous kernel on the product space of the cortex, and develop a method for estimating this kernel from tractography fiber models. Next, we formulate the kernel registration problem, and present a means to non-linearly register two brains' continuous connectivity profiles. We apply theoretical results from operator theory to develop an algorithm for decomposing the connectome into its shared and individual components. Lastly, we extend two discrete connectivity measures to the continuous case, and apply our framework to 98 Alzheimer's patients and controls. Our measures show significant differences between the two groups. © 2014 Springer International Publishing.
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Gutman, B., Leonardo, C., Jahanshad, N., Hibar, D., Eschenburg, K., Nir, T., … Thompson, P. (2014). Registering cortical surfaces based on whole-brain structural connectivity and continuous connectivity analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8675 LNCS, pp. 161–168). Springer Verlag. https://doi.org/10.1007/978-3-319-10443-0_21
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