BEH: Bangladesh Eye Hospital Glaucoma Dataset

Fundus photographs from Bangladesh Eye Hospital for glaucoma detection. Includes optic cup/disc crops and vessel segmentation masks alongside binary glaucoma/normal labels.

At a glance

Field	Value
Short name	beh
Full name	BEH: Bangladesh Eye Hospital Glaucoma Dataset
Primary category	fundus
Contained modalities	fundus
Tasks	classification, segmentation
Samples	634
Classes	2 (Normal, Glaucoma)
Splits	train, test
Size	0.3 GB
Source-stated terms	Research only
Normalized terms	research-only
Descriptive screening label	Research or challenge restriction recorded; check source
Terms scope	dataset_files
Access friction	anonymous_direct
Route backend	Google Drive
Availability	available (checked 2026-07-21)
Acquisition support	loader_implemented_not_live_tested
Legacy sample-loader status	Standard loader included

Access preflight and acquisition

CLI

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

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

Python

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

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

Upstream page: drive.google.com/file

Source-term evidence: drive.google.com/file

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

Citation

BibTeX

@misc{beh,
  title  = { BEH: Bangladesh Eye Hospital Glaucoma Dataset },
  note   = { Islam MT et al., 'Deep Learning-Based Glaucoma Detection with Cropped Optic Cup and Disc and Blood Vessel Segmentation', IEEE Access 2022. https://github.com/mirtanvirislam/Deep-Learning-Based-Glaucoma-Detection-with-Cropped-Optic-Cup-and-Disc-and-Blood-Vessel-Segmentation },
  year   = { 2022 },
  url    = { https://drive.google.com/file/d/1YdZm-sioiAbTdBRy4oej1q6tZL8Baft7 },
}

Plain text

Islam MT et al., 'Deep Learning-Based Glaucoma Detection with Cropped Optic Cup and Disc and Blood Vessel Segmentation', IEEE Access 2022. https://github.com/mirtanvirislam/Deep-Learning-Based-Glaucoma-Detection-with-Cropped-Optic-Cup-and-Disc-and-Blood-Vessel-Segmentation

Source-stated terms

• Raw source string: Research only
• Normalized category: research-only
• Apparent scope: dataset_files
• Descriptive screening label: Research or challenge restriction recorded; check source

⚠️ 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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