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DRIVE: Digital Retinal Images for Vessel Extraction

Forty color fundus photographs from a diabetic retinopathy screening program, divided into 20 training and 20 test images, with vessel reference annotations and field of view masks.

At a glance

FieldValue
Short namedrive
Full nameDRIVE: Digital Retinal Images for Vessel Extraction
Primary categoryfundus
Contained modalitiesfundus
Taskssegmentation
Samples40
Classes2 (background, vessel)
Splitstrain, test
SizeNot reported
Source-stated termsUnknown; no named dataset license on the official page
Normalized termsunknown
Descriptive screening labelUnknown or unclear; do not assume permission
Terms scopeunknown
Access frictionself_service_authenticated
Route backendManual (upstream-gated)
Availabilityavailable (checked 2026-07-21)
Acquisition supportguided_instructions_only
Legacy sample-loader statusMetadata and access only

Notes

The official page reports 768 by 584 pixel images, one manual vessel segmentation for each training image, and hidden test references used by the evaluation server. Verify reuse terms with the source before redistribution.

Access preflight and acquisition

# Read-only preflight
eyehub download drive --data-dir ./data --dry-run --json

# Explicit transfer, only when preflight reports supported behavior
eyehub download drive --data-dir ./data

Upstream page: drive.grand-challenge.org/DRIVE

Source-term evidence: drive.grand-challenge.org/DRIVE

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

@misc{drive,
title = { DRIVE: Digital Retinal Images for Vessel Extraction },
note = { Staal J, Abramoff MD, Niemeijer M, Viergever MA, van Ginneken B. Ridge-based vessel segmentation in color images of the retina. IEEE Trans Med Imaging. 2004;23:501-509. doi:10.1109/TMI.2004.825627 },
year = { 2004 },
url = { https://drive.grand-challenge.org/DRIVE/ },
}

Source-stated terms

  • Raw source string: Unknown; no named dataset license on the official page
  • Normalized category: unknown
  • Apparent scope: unknown
  • Descriptive screening label: Unknown or unclear; do not assume permission

⚠️ 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.

  • 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)