UMN Parhi Lab AMD OCT Fluid Segmentation Dataset

600 Spectralis OCT B-scans from 24 exudative AMD subjects. Three fluid region classes: IRF, SRF, PED. Dual expert annotation.

At a glance

Field	Value
Short name	umn_parhi_oct
Full name	UMN Parhi Lab AMD OCT Fluid Segmentation Dataset
First published	Unknown
Publication date precision	Unknown
Publication date evidence	Unknown
Publication date source field	Unknown
Publication date reviewed	Unknown
Primary category	oct
Resource role	current_dataset
Dataset family	umn_parhi_oct
Contained modalities	oct
Tasks	segmentation
Primary reported quantity	600 images
Classes	3 (IRF, SRF, PED)
Splits	all
Size	0.5 GB
Source-stated terms	Academic research use (University of Minnesota)
Normalized terms	research-only
Descriptive screening label	Research or challenge restriction recorded; check source
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	600	images	Primary quantity reported in the reviewed catalog source	legacy_catalog_field	people.ece.umn.edu/users

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 umn_parhi_oct --data-dir ./data --dry-run --json

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

Python

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

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

Upstream page: people.ece.umn.edu/users

Source-term evidence: people.ece.umn.edu/users

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

Citation

BibTeX

@misc{umn_parhi_oct,
  title  = { UMN Parhi Lab AMD OCT Fluid Segmentation Dataset },
  note   = { Parhi Lab OCT AMD Fluid Dataset. http://people.ece.umn.edu/users/parhi/data-and-code/ },
  url    = { http://people.ece.umn.edu/users/parhi/.DATA/OCT/DME/UMNDataset.mat },
}

Plain text

Parhi Lab OCT AMD Fluid Dataset. http://people.ece.umn.edu/users/parhi/data-and-code/

Source-stated terms

• Raw source string: Academic research use (University of Minnesota)
• 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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