In this study, we present a refined xf-irOCM system and post-processing pipeline for detailed investigation
of cerebral vessel structure and function. Our method uses deep learning for 3D segmentation of high-
resolution angiograms and accurately estimates flow velocities across the cerebral vasculature. Our graph-
based approach uniquely enables multiscale assessments, capturing data from intricate capillaries to broad
network relationships. Specifically, it aids in understanding vascular alterations in neurovascular
pathologies, such as stroke. Our approach will pave the way for future microvasculature studies, offering
promising avenues for further research into neurovascular diseases.
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