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ACE Dataset
ACE (Automated Cyst Evaluation) is a curated collection of 2,266 Optical Coherence Tomography (OCT) B-scans obtained from 40 patients diagnosed with <span clas
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views175
Total Downloads8
ACE (Automated Cyst Evaluation) is a curated collection of 2,266 Optical Coherence Tomography (OCT) B-scans obtained from 40 patients diagnosed with Diabetic Macular Edema (DME). It is specifically designed to support the development and validation of deep learning models for two primary tasks: segmentation of intraretinal cysts and clinical grading of disease severity.
Key Features of the Dataset:
- Dual Annotation: Each B-scan is paired with a high-resolution binary mask for precise cyst delineation and a clinical grade assigned by expert ophthalmologists.
- Clinical Standards: Grading follows the ESASO (European School for Advanced Studies in Ophthalmology) criteria, categorizing scans into four severity levels: Class 0 (Absent), Class 1 (Mild), Class 2 (Moderate), and Class 3 (Severe).
- Patient-Level Structure: To prevent overfitting to specific anatomical features and ensure model generalizability, the data is organized with an explicit patient-level subdivision<sup class="superscri
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Files are hosted on the source repository. Click download to access the full dataset.
Amato, Domenico (2026). ACE Dataset. https://doi.org/10.5281/zenodo.15234408