FIVES: Fundus Image Vessel Segmentation

800 high-resolution (2048x2048) fundus images with pixel-wise vessel segmentation. Covers normal, DR, AMD, glaucoma.

At a glance

Field	Value
Short name	fives
Full name	FIVES: Fundus Image Vessel Segmentation
Primary category	fundus
Contained modalities	fundus
Tasks	segmentation
Samples	800
Classes	Not reported (Not reported)
Splits	train, test
Size	1.1 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	Standard loader included

Access preflight and acquisition

CLI

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

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

Python

from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY

ds = REGISTRY.get_dataset('fives')
print(preflight_dataset(ds, './data'))  # no transfer

Upstream page: https://doi.org/10.6084/m9.figshare.19688169

Source-term evidence: https://doi.org/10.6084/m9.figshare.19688169

Loader example

This entry includes a standard DatasetSample loader.

from pathlib import Path
from eyedatahub.datasets.registry import REGISTRY

data_dir = Path('~/.eyedatahub/data').expanduser()
ds = REGISTRY.get_dataset('fives')
samples = ds.load(data_dir, split='test')
for s in samples[:5]:
    print(s.sample_id, s.label, s.image_path)

Citation

BibTeX

@misc{fives,
  title  = { FIVES: Fundus Image Vessel Segmentation },
  note   = { Jin et al., 'FIVES: A Fundus Image Dataset for Artificial Intelligence based Vessel Segmentation', Scientific Data 2022 },
  year   = { 2022 },
  url    = { https://doi.org/10.6084/m9.figshare.19688169 },
}

Plain text

Jin et al., 'FIVES: A Fundus Image Dataset for Artificial Intelligence based Vessel Segmentation', Scientific Data 2022.

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.

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