Abstract
3D optical coherence tomography angiography (OCT-A) is a novel, non-invasive imaging modality for studying important retina-related diseases. Current works have been mainly focusing on the microvascular analysis of 2D enface OCT-A projections while direct 3D analysis using rich depth-resolved microvascular information is rarely considered. In this work, we aim to set up an innovative 3D microvascular modeling framework via Reeb analysis to explore rich geometric and topological information. We first use effective vessel extraction and surface reconstruction techniques to establish a complete 3D mesh representation of retinal OCT-A microvasculature. We propose to use geodesic distance as a feature function to build level contours with smooth transitions on mesh surface. Intrinsic Reeb graphs are thereby constructed through level contours to represent general OCT-A microvascular topology. Afterwards, specific geometric and topological analysis are performed on Reeb graphs to quantify critical microvascular characteristics. The proposed Reeb analysis framework is evaluated on a clinical DR dataset and shows great advantage in describing 3D microvascular changes. It is able to produce important surface-based microvascular biomarkers with high statistical power for disease studies.
Y. Shi—This work was supported in part by NIH grants UH3NS100614, R21EY027879, U01EY025864, K08EY027006, P41EB015922, P30EY029220, and Research to Prevent Blindness.
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Zhang, J., Kashani, A.H., Shi, Y. (2019). 3D Surface-Based Geometric and Topological Quantification of Retinal Microvasculature in OCT-Angiography via Reeb Analysis. In: Shen, D., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science(), vol 11764. Springer, Cham. https://doi.org/10.1007/978-3-030-32239-7_7
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