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Proceedings Paper

Cortical connectome registration using spherical demons
Author(s): Dmitry Isaev; Boris A. Gutman; Daniel Moyer; Joshua Faskowitz; Paul M. Thompson
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Paper Abstract

We present an algorithm to align cortical surface models based on structural connectivity. We follow the continuous connectivity approach,1, 2 assigning a dense connectivity to every surface point-pair. We adapt and modify an approach for aligning low-rank functional networks based on eigenvalue decomposition of individual connectomes.3 The spherical demons framework then provides a natural setting for inter-subject connectivity alignment, enforcing a smooth, anatomically plausible correspondence, and allowing us to incorporate anatomical as well as connectivity information. We apply our algorithm to 98 diffusion MRI images in an Alzheimer's Disease study, and 731 healthy subjects from the Human Connectome Project. Our method consistently reduces connectome variability due to misalignment. Further, the approach reveals subtle disease effects on structural connectivity which are not seen when registering only cortical anatomy.

Paper Details

Date Published: 26 January 2017
PDF: 9 pages
Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 101600M (26 January 2017); doi: 10.1117/12.2256975
Show Author Affiliations
Dmitry Isaev, The Univ. of Southern California (United States)
Boris A. Gutman, The Univ. of Southern California (United States)
Daniel Moyer, The Univ. of Southern California (United States)
Joshua Faskowitz, The Univ. of Southern California (United States)
Paul M. Thompson, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 10160:
12th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Jorge Brieva; Ignacio Larrabide; , Editor(s)

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