ERDES: Eye Retinal Detachment Ultrasound Dataset

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Dataset
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📌 Introduction

ERDES is a large-scale, publicly available dataset of 3D ocular ultrasound videos for retinal and macular detachment classification. It was introduced in our paper ERDES: A Benchmark Video Dataset for Retinal Detachment and Macular Status Classification in Ocular Ultrasound. The corpus consists of 5,381 expertly annotated video clips totaling 5 hours and 10 minutes, providing a valuable resource for medical AI research in ophthalmology.

Key Features:

• 5,381 labeled ultrasound video clips
• Expert annotations for retinal detachment (RD) and macular status
• Structured classification (Normal, RD, PVD, macula-detached/intact)
• Preprocessed for privacy and consistency

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🎯 Motivation

Medical video datasets for AI are scarce despite their clinical importance. ERDES bridges this gap by offering:

• A standardized benchmark for retinal detachment classification in ultrasound videos.
• Support for spatiotemporal analysis (e.g., 3D CNNs).
• Open access to accelerate research in ocular diagnostics.

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📊 Dataset Overview

1. Data Structure

Videos are categorized into two primary groups:

Non-RD (Non-Retinal Detachment):

• Normal
• Posterior Vitreous Detachment (PVD)

RD (Retinal Detachment):

• Macula-Detached
  • Bilateral (nasal and temporal regions involved)
  • Temporal detachment only
• Macula-Intact
  • Nasal detachment
  • Temporal detachment

2. Annotations

Each clip is labeled by sonologists for:

• Presence/absence of retinal detachment.
• Macular involvement (detached/intact).

3. Preprocessing

• Privacy: PHI removed using YOLOv8-based globe detection.
• Consistency: Cropped to the ocular ROI.
• Format: MP4 videos.

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📥 Download

Access the dataset via the HuggingFace API:

from datasets import load_dataset

dataset = load_dataset("pcvlab/erdes")

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🛠️ Code & Baselines

We open source our baseline experiments on our GitHub repo, which includes:

• Baseline 3D CNN and ViT models for classification.
• End-to-end diagnostic pipeline for macular detachment.

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📜 Citation

If you use ERDES, please cite:

@article{ozkuterdes,
  title={ERDES: A Benchmark Video Dataset for Retinal Detachment and Macular Status Classification in Ocular Ultrasound},
  author={Ozkut, Yasemin and Navard, Pouyan and Adhikari, Srikar and Situ-LaCasse, Elaine and Acu{\~n}a, Josie and Yarnish, Adrienne A and Yilmaz, Alper},
  journal={arXiv preprint arXiv:2508.04735},
  year={2025}
}