PALM — iChallenge Pathologic Myopia

1200 fundus images for pathologic myopia classification and optic disc / lesion segmentation. 50 % PM / 50 % non-PM.

At a glance

Field	Value
Short name	palm
Full name	PALM — iChallenge Pathologic Myopia
First published	2019-01-01
Publication date precision	day
Publication date evidence	palm.grand-challenge.org/Home
Publication date source field	Official PALM challenge Important Dates: Training images for the first classification task are released
Publication date reviewed	2026-09-11
Primary category	fundus
Resource role	current_dataset
Dataset family	palm
Contained modalities	fundus
Tasks	classification, segmentation
Primary reported quantity	1,200 images
Classes	2 (non-PM, PM)
Splits	train, val, test
Size	1.5 GB
Source-stated terms	Challenge data-use agreement (IEEE DataPort)
Normalized terms	research-only
Descriptive screening label	Research or challenge restriction recorded; check source
Terms scope	challenge_participation
Access friction	controlled_or_manual
Route backend	Google Drive
Availability	available (checked 2026-07-21)
Acquisition support	manual_access_blocked
Legacy sample-loader status	Standard loader included

Reported quantities

Role	Count	Unit	Scope	Basis	Evidence
Primary	1,200	images	Primary quantity reported in the reviewed catalog source	legacy_catalog_field	drive.google.com/file

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.

Documented relationships

These links record source-supported lineage or overlap, not merely similar modality tags.

• mm_retinal_reason is derived from this record: The version-pinned official dataset card lists this record among the CFP or OCT sources used to construct MM-Retinal-Reason. (evidence)

Access information and download

CLI

# This route requires upstream human action; no transfer starts.
eyehub download palm --data-dir ./data --dry-run --json
# Follow the official instructions shown by preflight.

Python

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

ds = REGISTRY.get_dataset('palm')
print(preflight_dataset(ds, './data'))  # returns manual_access_blocked

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

Citation

BibTeX

@misc{palm,
  title  = { PALM — iChallenge Pathologic Myopia },
  note   = { Fu H. et al., 'PALM: Pathologic Myopia Challenge', MICCAI 2019 Workshop },
  year   = { 2019 },
  url    = { https://drive.google.com/file/d/14XWD6kX0dVRfAyEc7FkZGKZibWEkvnyv/view },
}

Plain text

Fu H. et al., 'PALM: Pathologic Myopia Challenge', MICCAI 2019 Workshop.

Source-stated terms

• Raw source string: Challenge data-use agreement (IEEE DataPort)
• Normalized category: research-only
• Apparent scope: challenge_participation
• 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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