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Updated: Jan 20, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
Published on: December 15, 2023
Automated segmentation of peripapillary retinal boundaries in OCT combining a convolutional neural network and a
Pengxiao Zang1, Jie Wang1, Tristan T Hormel1
1Casey Eye Institute, Oregon Health & Science University, Portland, OR 97239, USA.
Abstract:
Quantitative analysis of the peripapillary retinal layers and capillary plexuses from optical coherence tomography (OCT) and OCT angiography images depend on two segmentation tasks - delineating the boundary of the optic disc and delineating the boundaries between retinal layers. Here, we present a method combining a neural network and graph search to perform these two tasks. A comparison of this novel method's segmentation of the disc boundary showed good agreement with the ground truth, achieving an overall Dice similarity coefficient of 0.91 ± 0.04 in healthy and glaucomatous eyes. The absolute error of retinal layer boundaries segmentation in the same cases was 4.10 ± 1.25 µm.
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