BRSET: Brazilian Multilabel Ophthalmological Dataset
16,266 color fundus images from 8,524 Brazilian patients with 14 disease labels (DR, AMD, glaucoma, drusen, others), image quality flags, and demographic attributes.
At a glance
| Field | Value |
|---|---|
| Short name | brset |
| Full name | BRSET: Brazilian Multilabel Ophthalmological Dataset |
| Primary category | fundus |
| Contained modalities | fundus |
| Tasks | multilabel, classification, quality |
| Samples | 16,266 |
| Classes | 14 (Not reported) |
| Splits | all |
| Size | 9.0 GB |
| Source-stated terms | PhysioNet Credentialed Health Data License 1.5.0 (Research only) |
| Normalized terms | research-only |
| Descriptive screening label | Research or challenge restriction recorded; check source |
| Terms scope | dataset_files |
| Access friction | controlled_or_manual |
| Route backend | PhysioNet |
| Availability | available (checked 2026-07-21) |
| Acquisition support | manual_access_blocked |
| Legacy sample-loader status | Metadata and access only |
Notes
Requires PhysioNet credentialed-user account + CITI training + signed Data Use Agreement. Set PHYSIONET_USERNAME and PHYSIONET_PASSWORD in .env to auto-download.
Access preflight and acquisition
- CLI
- Python
# This route requires upstream human action; no transfer starts.
eyehub download brset --data-dir ./data --dry-run --json
# Follow the official instructions shown by preflight.
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('brset')
print(preflight_dataset(ds, './data')) # returns manual_access_blocked
Upstream page: physionet.org/content
Source-term evidence: physionet.org/content
Loader status
This catalog record provides metadata and access instructions, but it does not yet include a standard DatasetSample loader. Inspect the source file structure or contribute a loader before using it in a training pipeline.
Citation
- BibTeX
- Plain text
@misc{brset,
title = { BRSET: Brazilian Multilabel Ophthalmological Dataset },
note = { Nakayama LF, Restrepo D, Matos J, et al., 'BRSET: A Brazilian Multilabel Ophthalmological Dataset of Retina Fundus Photos', PLOS Digital Health 3(7):e0000454, 2024. doi:10.1371/journal.pdig.0000454 · PhysioNet DOI: 10.13026/1pht-2b69 },
year = { 2024 },
url = { https://physionet.org/content/brazilian-ophthalmological/1.0.1/ },
}
Nakayama LF, Restrepo D, Matos J, et al., 'BRSET: A Brazilian Multilabel Ophthalmological Dataset of Retina Fundus Photos', PLOS Digital Health 3(7):e0000454, 2024. doi:10.1371/journal.pdig.0000454 · PhysioNet DOI: 10.13026/1pht-2b69
Source-stated terms
- Raw source string: PhysioNet Credentialed Health Data License 1.5.0 (Research only)
- Normalized category:
research-only - Apparent scope:
dataset_files - Descriptive screening label: Research or challenge restriction recorded; check source
⚠️ Source-stated terms, scope, and normalized labels are curation metadata, not legal advice or a permission finding. Review the current official source before transfer or reuse.
Related datasets with shared modalities
- airogs: AIROGS: AI for Robust Glaucoma Screening (113,893 records,
cc-by-nc-nd) - eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 records,
unknown) - justraigs: JustRAIGS: Just Referral AI Glaucoma Screening Dataset (101,442 records,
cc-by-nc-nd) - eyepacs: EyePACS — Diabetic Retinopathy Detection (Kaggle 2015) (88,702 records,
research-only) - multieye: MultiEYE: OCT-Enhanced Fundus Multi-Disease Benchmark (58,036 records,
mit) - angioreport: AngioReport Fundus Angiography Report Dataset (55,361 records,
unknown) - ffa_ir: FFA-IR Medical Report Dataset (47,247 records,
unknown) - bidr: BiDR: Diabetic Retinopathy Diagnosis Dataset (35,126 records,
unknown)