Harvard Glaucoma Fundus Image Dataset

Fundus images for glaucoma detection from Harvard Medical School / Mass Eye and Ear. Binary glaucoma classification.

At a glance

Field	Value
Short name	harvard_glaucoma
Full name	Harvard Glaucoma Fundus Image Dataset
First published	2018-11-15
Publication date precision	day
Publication date evidence	dataverse.harvard.edu/api
Publication date source field	Harvard Dataverse API: version 1.0 releaseTime
Publication date reviewed	2026-09-11
Primary category	fundus
Resource role	current_dataset
Dataset family	harvard_glaucoma
Contained modalities	fundus
Tasks	classification
Primary reported quantity	1,000 images
Classes	2 (Non-glaucoma, Glaucoma)
Splits	all
Size	1.5 GB
Source-stated terms	CC0 1.0 (Public Domain)
Normalized terms	cc0
Descriptive screening label	Standard label without an explicit NC clause; not a permission finding
Terms scope	dataset_files
Access friction	anonymous_direct
Route backend	Direct HTTP
Availability	available (checked 2026-07-21)
Acquisition support	end_to_end_tested
Legacy sample-loader status	Standard loader included

Reported quantities

Role	Count	Unit	Scope	Basis	Evidence
Primary	1,000	images	Primary quantity reported in the reviewed catalog source	legacy_catalog_field	https://doi.org/10.7910/DVN/1YRRAC

Counts retain their source-reported units. Additional rows can describe components, paired items, or derivative copies and are not automatically added to the primary quantity.

Access information and download

CLI

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

# Download, only when preflight reports supported behavior
eyehub download harvard_glaucoma --data-dir ./data

Python

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

ds = REGISTRY.get_dataset('harvard_glaucoma')
print(preflight_dataset(ds, './data'))  # no download

Upstream page: https://doi.org/10.7910/DVN/1YRRAC

Source-term evidence: https://doi.org/10.7910/DVN/1YRRAC

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('harvard_glaucoma')
samples = ds.load(data_dir, split='all')
for s in samples[:5]:
    print(s.sample_id, s.label, s.image_path)

Citation

BibTeX

@misc{harvard_glaucoma,
  title  = { Harvard Glaucoma Fundus Image Dataset },
  note   = { Luo X. et al., 'Harvard Glaucoma Detection and Progression Dataset', Harvard Dataverse, doi:10.7910/DVN/1YRRAC, 2023 },
  year   = { 2023 },
  url    = { https://doi.org/10.7910/DVN/1YRRAC },
}

Plain text

Luo X. et al., 'Harvard Glaucoma Detection and Progression Dataset', Harvard Dataverse, doi:10.7910/DVN/1YRRAC, 2023.

Source-stated terms

• Raw source string: CC0 1.0 (Public Domain)
• Normalized category: cc0
• 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.

Similar resources by shared modality

• airogs: AIROGS: AI for Robust Glaucoma Screening (113,893 images, cc-by-nc-nd)
• multieye: MultiEYE: OCT-Enhanced Fundus Multi-Disease Benchmark (103,959 images, mit)
• eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 question answer pairs, unknown)
• justraigs: JustRAIGS: Just Referral AI Glaucoma Screening Dataset (101,442 images, cc-by-nc-nd)
• eyepacs: EyePACS — Diabetic Retinopathy Detection (Kaggle 2015) (88,702 images, research-only)
• angioreport: AngioReport Fundus Angiography Report Dataset (55,361 images, unknown)
• ffa_ir: FFA-IR Medical Report Dataset (47,247 images, unknown)
• mfiddr: MFIDDR: Multi-Field Imaging Dataset for Diabetic Retinopathy (34,452 images, mit)