Automated segmentation and quantification of OCT angiography for tracking angiogenesis progression

Biomedical Optics Express
Ang LiYingtian Pan

Abstract

Angiogenesis is recognized as a crucial component of many neurovascular diseases such as stroke, carcinogenesis, and neurotoxicity of abused drug. The ability to track angiogenesis will facilitate a better understanding of disease progression and assessment of therapeutical effects. Optical coherence angiography (OCTA) is a promising tool to assess 3D microvascular networks due to its micron-level resolution, high sensitivity, and relatively large field of view. However, quantitative OCTA image analysis for characterization of microvascular network changes, including accurately tracking the progression of angiogenesis, remains a challenge. In this paper, we proposed an angiogenesis tracking algorithm which combines improved vessel segmentation and brain boundary detection methods to significantly enhance time-lapse OCTA images for quantification of microvascular network changes. Specifically, top-hat enhancement and optimally oriented flux (OOF) algorithms facilitated accurate segmentation of cerebrovascular networks (including capillaries); graph-search based brain boundary detection enabled coregistration of 3D OCTA data sets from different time points for accurate vessel density assessment and analysis of their changes in va...Continue Reading

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Citations

Sep 29, 2018·Journal of Experimental Neuroscience·Oana M Dumitrascu, Touseef A Qureshi
Sep 18, 2018·Applied Physics Letters·Ang LiYingtian Pan
Aug 29, 2020·Translational Vision Science & Technology·Julian LoMarinko V Šarunić
Dec 22, 2020·Translational Vision Science & Technology·Ylenia GiarratanoMiguel O Bernabeu
Jun 16, 2021·Lasers in Surgery and Medicine·Farah AndleebThomas E Milner
Jul 6, 2021·Frontiers in Immunology·Lydia J BradleyLindsay B Nicholson

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