Generative Artificial Intelligence for Retinal Image Translation to Improve Glaucoma Screening With Deep Learning
GANs may improve glaucoma classification models by improving dataset consistency and mitigating domain shifts. By generating synthetic CF images from SLO data, GANs expand available training data in a clinically relevant imaging modality.
Authors
- Iyad Majid (ORCID: https://orcid.org/0000-0003-2447-8271)
- Nazlee Zebardast (ORCID: https://orcid.org/0000-0003-1763-9401)
- Mengyu Wang (ORCID: https://orcid.org/0009-0003-3104-7725)
Institutions
- Massachusetts Eye and Ear Infirmary (US)
- Harvard University (US)
- Smith-Kettlewell Eye Research Institute (US)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-11-21
- DOI
- https://doi.org/10.1167/tvst.14.11.36
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00