AFIO Fundus Images for Vessel Segmentation and Disease Annotation
One hundred retinal fundus images from Armed Forces Institute of Ophthalmology, Rawalpindi, with expert annotations for vessels and hypertensive retinopathy, diabetic retinopathy, and papilledema tasks.
At a glance
| Field | Value |
|---|---|
| Short name | afio_fundus_vessels |
| Full name | AFIO Fundus Images for Vessel Segmentation and Disease Annotation |
| Primary category | fundus |
| Contained modalities | fundus |
| Tasks | segmentation, classification |
| Samples | 100 |
| Classes | Not reported (Not reported) |
| Splits | all |
| Size | 0.2 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 | Mendeley Data |
| Availability | available (checked 2026-07-21) |
| Acquisition support | standard_platform_supported |
| Legacy sample-loader status | Metadata and access only |
Notes
Mendeley Data may block automated URL probes with HTTP 403 (no bot allowed); browser link is valid.
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download afio_fundus_vessels --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download afio_fundus_vessels --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('afio_fundus_vessels')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: data.mendeley.com/datasets
Source-term evidence: data.mendeley.com/datasets
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{afio_fundus_vessels,
title = { AFIO Fundus Images for Vessel Segmentation and Disease Annotation },
note = { Akram MU et al. Data on Fundus Images for Vessels Segmentation, Detection of Hypertensive Retinopathy, Diabetic Retinopathy and Papilledema. Mendeley Data, V2, 2019. doi:10.17632/3csr652p9y.2 },
year = { 2019 },
url = { https://data.mendeley.com/datasets/3csr652p9y/2 },
}
Akram MU et al. Data on Fundus Images for Vessels Segmentation, Detection of Hypertensive Retinopathy, Diabetic Retinopathy and Papilledema. Mendeley Data, V2, 2019. doi:10.17632/3csr652p9y.2
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
- 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)