Cortical connectome registration using spherical demons

Dmitry Isaev; Boris A. Gutman; Daniel Moyer; Joshua Faskowitz; Paul M. Thompson

doi:10.1117/12.2256975

26 January 2017 Cortical connectome registration using spherical demons

Dmitry Isaev, Boris A. Gutman, Daniel Moyer, Joshua Faskowitz, Paul M. Thompson

Proceedings Volume 10160, 12th International Symposium on Medical Information Processing and Analysis; 101600M (2017) https://doi.org/10.1117/12.2256975
Event: 12th International Symposium on Medical Information Processing and Analysis, 2016, Tandil, Argentina

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.

Citation Download Citation

Dmitry Isaev, Boris A. Gutman, Daniel Moyer, Joshua Faskowitz, and Paul M. Thompson "Cortical connectome registration using spherical demons", Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 101600M (26 January 2017); https://doi.org/10.1117/12.2256975

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