Published March 12, 2026
| Version v1
Dataset
Open
Synthetic Retinal OCT Dataset Generated using Class-Conditioned DDPM
Authors/Creators
Description
This dataset contains synthetic Optical Coherence Tomography (OCT) retinal images generated using class conditioned denoising diffusion probabilistic models (DDPMs). The images represent four diagnostic categories: choroidal neovascularization (CNV), diabetic macular edema (DME), drusen, and normal retina. Synthetic data are generated to address the limited availability of labeled OCT datasets and support the development of AI models for retinal disease classification. The generated images aim to preserve realistic retinal structures and disease characteristics for machine learning research.
Files
generated_images.zip
Files
(36.1 MB)
| Name | Size | Download all |
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md5:7a9ee3ba5a0960c678f0b04bcd80576c
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36.1 MB | Preview Download |
Additional details
Dates
- Accepted
-
2026-03-12