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Updated: Jun 8, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation
Stephanie J Chiu1, Xiao T Li, Peter Nicholas
1Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA. stephanie.chiu@duke.edu
Abstract:
Segmentation of anatomical and pathological structures in ophthalmic images is crucial for the diagnosis and study of ocular diseases. However, manual segmentation is often a time-consuming and subjective process. This paper presents an automatic approach for segmenting retinal layers in Spectral Domain Optical Coherence Tomography images using graph theory and dynamic programming. Results show that this method accurately segments eight retinal layer boundaries in normal adult eyes more closely to an expert grader as compared to a second expert grader.