SYN-OCT
Damon Wong,
Ashish Jith Sreejith Kumar,
Rachel S. Chong,
Monisha E. Nongpiur,
Rahat Hussain,
Tina Wong,
Shamira Pereira,
Tin Aung,
Bingyao Tan,
Ching-Yu Cheng,
Eranga Vithana N,
Jacqueline Chua,
Leopold Schmetterer
License
No license available
The SYN-OCT dataset consists of 200,000 synthetic cross-sectional circumpapillary OCT images, including 100,000 images generated to represent glaucoma eyes and 100,000 images generated to represent healthy eyes. These synthetic images were produced using generative models trained on real OCT scans collected from participants at the Singapore Eye Research Institute. This resource is designed to support the development and validation of deep learning models for glaucoma detection and analysis. It also serves as a landmark dataset for advancing research on synthetic medical image generation and its potential applications in clinical and AI settings.