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ReLayer: a free, online tool for extracting retinal thickness from cross-platform OCT images

Ometto, G., Moghul, I., Montesano, G., Hunter, A., Pontikos, N., Jones, P. R. ORCID: 0000-0001-7672-8397, Keane, P. A., Xioxuan, L., Denniston, A. K. and Crabb, D. P. (2019). ReLayer: a free, online tool for extracting retinal thickness from cross-platform OCT images. Translational Vision Science & Technology, 8(3), 25.. doi: 10.1167/tvst.8.3.25

Abstract

Purpose: To describe and evaluate a free, online tool for automatically segmenting optical coherence tomography (OCT) images from different devices and computing summary measures such as retinal thickness.

Methods: ReLayer (https://relayer.online) is an online platform to which OCT scan images can be uploaded and analyzed. Results can be downloaded as plaintext (.csv) files. The segmentation method includes a novel, 1-dimensional active contour model, designed to locate the inner limiting membrane, inner/outer segmentand retinal pigment epithelium. The method, designed for B-scans from Heidelberg Engineering Spectralis, was adapted for Topcon 3D OCT-2000 and OptoVue AngioVue. The method was applied to scans from healthy and pathological eyes, and was validated against segmentation by the manufacturers, the 39IOWA Reference Algorithms,and manual segmentation.

Results: Segmentation of a B-scan took≤ 1 second. In healthy eyes, mean difference in retinal thickness from ReLayer and the reference standard was below the resolution of the Spectralis and 3D OCT-2000, and slightly above the resolution of the AngioVue. In pathological eyes, ReLayer performed similarly to IOWA (p=0.97) and better than Spectralis (p<0.001).

Publication Type: Article
Additional Information: Copyright 2019, The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Publisher Keywords: optical coherence tomography; image analysis; segmentation
Subjects: R Medicine > RE Ophthalmology
Departments: School of Health Sciences > Optometry & Visual Science
URI: http://openaccess.city.ac.uk/id/eprint/22016
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