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The glymphatic system (GS) is a transit passage that facilitates brainmetabolic waste removal and its dysfunction has been associated withneurodegenerative diseases such as Alzheimer's disease. The GS has been studiedby acquiring temporal contrast enhanced magnetic resonance imaging (MRI)sequences of a rodent brain, and tracking the cerebrospinal fluid injectedcontrast agent as it flows through the GS. We present here a novelvisualization framework, GlymphVIS, which uses regularized optimal transport(OT) to study the flow behavior between time points at which the images aretaken. Using this regularized OT approach, we can incorporate diffusion, handlenoise, and accurately capture and visualize the time varying dynamics in GStransport. Moreover, we are able to reduce the registration mean-squared andinfinity-norm error across time points by up to a factor of 5 as compared tothe current state-of-the-art method. Our visualization pipeline yields flowpatterns that align well with experts' current findings of the glymphaticsystem.

GlymphVIS: Visualizing Glymphatic Transport Pathways Using Regularized Optimal Transport