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The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation

Open access
Chiu, Stephanie J., Li, Xiao T., Nicholas, Peter, Toth, Cynthia A., Izatt, Joseph A., Farsiu, Sina·2010·Optics Express

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.

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Crossref · 10.1364/oe.18.019413

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Metadata

Authors
Chiu, S. J., Li, X. T., Nicholas, P., Toth, C. A., Izatt, J. A., & Farsiu, S.
Venue
Optics Express
Published
2010-08-27
Volume
18
Issue
18
Pages
19413
ISSN
1094-4087 (ISSN-L)
OpenAlex
W2011237852
Cited by
733
References
16
FWCI
15.67
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation. https://app.cochat.ai/papers/10.1364/oe.18.019413
The paper
Chiu, S. J., Li, X. T., Nicholas, P., Toth, C. A., Izatt, J. A., & Farsiu, S. (2010). Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation. Optics Express. https://doi.org/10.1364/oe.18.019413

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.