Presentation
13 March 2024 Bessel-beam OCM enables multiscale precision assessment of deep brain morpho-functional vessel changes
Author Affiliations +
Abstract
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.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lukas B. Glandorf, Bastian Wittmann, Jeanne Droux, Chaim Glueck, Bruno Weber, Susanne Wegener, Mohamad El-Amki, Rainer Leitgeb, Bjoern Menze, and Daniel Razansky "Bessel-beam OCM enables multiscale precision assessment of deep brain morpho-functional vessel changes", Proc. SPIE PC12830, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVIII, PC128302I (13 March 2024); https://doi.org/10.1117/12.3005633
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KEYWORDS
Brain

Cerebrovascular diseases

Brain diseases

Capillaries

Deep learning

Doppler effect

In vivo imaging

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