Deriving OCT-Equivalent Retinal Nerve Fiber Layer Thickness Maps from Fundus Photographs with Deep Learning Improves Glaucoma Diagnosis.
- DOI
- 10.1016/j.xops.2026.101325
- Published
- 2026 Oct
- Container
- Ophthalmology science
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.xops.2026.101325,
title = {Deriving OCT-Equivalent Retinal Nerve Fiber Layer Thickness Maps from Fundus Photographs with Deep Learning Improves Glaucoma Diagnosis.},
author = {Shi L and Shi M and Chung IY and Pasquale LR and Shen LQ and Wang M},
year = {2026},
journal = {Ophthalmology science},
doi = {10.1016/j.xops.2026.101325},
url = {https://doi.org/10.1016/j.xops.2026.101325}
}RIS
TY - JOUR TI - Deriving OCT-Equivalent Retinal Nerve Fiber Layer Thickness Maps from Fundus Photographs with Deep Learning Improves Glaucoma Diagnosis. AU - Shi L AU - Shi M AU - Chung IY AU - Pasquale LR AU - Shen LQ AU - Wang M PY - 2026 JO - Ophthalmology science DO - 10.1016/j.xops.2026.101325 UR - https://doi.org/10.1016/j.xops.2026.101325 ER -
APA
L, S., M, S., IY, C., LR, P., LQ, S., & M, W. (2026). Deriving OCT-Equivalent Retinal Nerve Fiber Layer Thickness Maps from Fundus Photographs with Deep Learning Improves Glaucoma Diagnosis.. Ophthalmology science. https://doi.org/10.1016/j.xops.2026.101325
Source records
- pubmed · retrieved 2026-09-25T21:38:55.782Z