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. 2021 Jan 13;11:1212. doi: 10.1038/s41598-020-80099-2

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Image processing technique using an in-house automated programme written in MATLAB (Mathworks, Inc., Natick, MA, USA); the region of interest (ROI) is the area demarcated by the dotted line. (A) Example of corneal vascularisation captured using anterior segment optical coherence tomography (AS-OCT) angiography (Nidek RS-3000, Tokyo, Japan); (B) the overlay image is binarized at the ROI where white pixels represented the blood vessels and black represented the background—vessel density (VD) is the area of white pixels as a percentage of the whole binarized image; (C) Skeletonization of the binarized images, where all the vessel segments were reduced to one pixel-wide segment—vessel branch area (VBA) is the total length of the vessel branch as a percentage of the whole binarized image; the VD as a percentage of the VBA, represents the vessel width of the corneal vessels in the ROI.