Elkin, RenaNadeem, SaadHaber, EldadSteklova, KlaraLee, HedokBenveniste, HeleneTannenbaum, Allen2025-06-242025-06-2497830300092740302-9743ORCID:/0000-0002-6912-1375/work/167653148http://www.scopus.com/inward/record.url?scp=85054075436&partnerID=8YFLogxKhttps://hdl.handle.net/1885/733764903The glymphatic system (GS) is a transit passage that facilitates brain metabolic waste removal and its dysfunction has been associated with neurodegenerative diseases such as Alzheimer’s disease. The GS has been studied by acquiring temporal contrast enhanced magnetic resonance imaging (MRI) sequences of a rodent brain, and tracking the cerebrospinal fluid injected contrast agent as it flows through the GS. We present here a novel visualization framework, GlymphVIS, which uses regularized optimal transport (OT) to study the flow behavior between time points at which the images are taken. Using this regularized OT approach, we can incorporate diffusion, handle noise, and accurately capture and visualize the time varying dynamics in GS transport. Moreover, we are able to reduce the registration mean-squared and infinity-norm error across time points by up to a factor of 5 as compared to the current state-of-the-art method. Our visualization pipeline yields flow patterns that align well with experts’ current findings of the glymphatic system.This project was supported by AFOSR grant FA9550-17-1-0435), ARO grant (W911NF-17-1-049), grants from National Institutes of Health (1U24CA1809240 1A1, R01-AG048769), MSK Cancer Center Support Grant/Core Grant (P30 CA008748), and a grant from Breast Cancer Research Foundation (grant BCRF-17-193).9enPublisher Copyright: © Springer Nature Switzerland AG 2018.201810.1007/978-3-030-00928-1_9585054075436