MCOA: Multimodal Corneal Opacity Assessment Dataset
6,272 AS-OCT images + 392 anterior-segment photographs for corneal opacity assessment with expert grading. First large public multimodal AS-OCT + photo dataset for cornea.
At a glance
| Field | Value |
|---|---|
| Short name | mcoa |
| Full name | MCOA: Multimodal Corneal Opacity Assessment Dataset |
| Primary category | multimodal |
| Contained modalities | oct, external_eye |
| Tasks | classification, grading |
| Samples | 6,664 |
| Classes | 4 (Not reported) |
| Splits | all |
| Size | 8.0 GB |
| Source-stated terms | CC BY 4.0 |
| Normalized terms | cc-by |
| Descriptive screening label | Standard label without an explicit NC clause; not a permission finding |
| Terms scope | dataset_files |
| Access friction | anonymous_direct |
| Route backend | Figshare |
| Availability | available (checked 2026-07-21) |
| Acquisition support | transfer_tested_partial |
| Legacy sample-loader status | Metadata and access only |
Notes
Anterior-segment expansion; modality otherwise sparse.
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download mcoa --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download mcoa --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('mcoa')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: https://doi.org/10.6084/m9.figshare.28123088.v1
Source-term evidence: https://doi.org/10.6084/m9.figshare.28123088.v1
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{mcoa,
title = { MCOA: Multimodal Corneal Opacity Assessment Dataset },
note = { Ma X, et al., 'MCOA: A comprehensive multimodal dataset for advancing deep learning in corneal opacity assessment', Scientific Data 2025 },
year = { 2025 },
url = { https://doi.org/10.6084/m9.figshare.28123088.v1 },
}
Ma X, et al., 'MCOA: A comprehensive multimodal dataset for advancing deep learning in corneal opacity assessment', Scientific Data 2025.
Source-stated terms
- Raw source string: CC BY 4.0
- Normalized category:
cc-by - Apparent scope:
dataset_files - Descriptive screening label: Standard label without an explicit NC clause; not a permission finding
⚠️ 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
- eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 records,
unknown) - lmod_plus: LMOD+ Multimodal Ophthalmology Benchmark (32,633 records,
unknown) - x_pcr: X-PCR Ophthalmology Progressive Clinical Reasoning Benchmark (18,700 records,
unknown) - ophthalvqa: OphthalVQA Dataset (count not reported records,
cc-by) - syn_oct: SYN-OCT Synthetic Glaucoma OCT Dataset (200,000 records,
cc-by) - kermany_oct: Kermany OCT 2018: Retinal OCT Image Classification (84,484 records,
cc-by) - multieye: MultiEYE: OCT-Enhanced Fundus Multi-Disease Benchmark (58,036 records,
mit) - harvard_fairvision: Harvard-FairVision (AMD + DR + Glaucoma, paired SLO + OCT) (30,000 records,
cc-by-nc-nd)