Tunisian OCT Dataset for Multi-Disease Retinal ClassificationTunisian OCT Dataset for Multi-Disease Retinal Classification

The Retinal-OCT-Clinical-Dataset is a collection of clinically acquired retinal OCT (Optical Coherence Tomography) images, designed to serve as a benchmark for deep learning models in retinal disease classification.
The dataset includes images from multiple retinal pathologies:
AMD (Age-related Macular Degeneration)
DME (Diabetic Macular Edema)
RRD (Rhegmatogenous Retinal Detachment)
Healthy/Normal cases
⚠️ Access: To ensure compliance with ethical guidelines and patient privacy, the dataset is available upon reasonable request under controlled access conditions.
This dataset is suitable for:
Training and evaluating deep learning models for retinal disease detection.
Benchmarking classification performance across multiple retinal pathologies.

Access to the dataset is granted after approval of a signed Data Use Agreement.
The Data Agreement is available on the project GitHub repository.
Applicants must download the agreement, sign it, and send it by email to: zainab.haddad@enit.utm.tn
After approval, download access will be granted manually.