MARIO: AMD-Progression Longitudinal OCT (MICCAI 2024)
~30,000 longitudinal OCT B-scans across multiple patient visits, annotated for AMD change detection and progression monitoring.
At a glance
| Field | Value |
|---|---|
| Short name | mario |
| Full name | MARIO: AMD-Progression Longitudinal OCT (MICCAI 2024) |
| 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 | mario |
| Contained modalities | oct |
| Tasks | classification, progression |
| Primary reported quantity | 30,000 images |
| Classes | 4 (Not reported) |
| Splits | train, val, test |
| Size | 25.0 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 | self_service_authenticated |
| Route backend | Zenodo |
| Availability | available (checked 2026-07-21) |
| Acquisition support | standard_platform_supported |
| Legacy sample-loader status | Metadata and access only |
Reported quantities
| Role | Count | Unit | Scope | Basis | Evidence |
|---|---|---|---|---|---|
| Primary | 30,000 | images | Primary quantity reported in the reviewed catalog source | legacy_catalog_field | zenodo.org/records |
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.
Notes
Distributed as 21 multi-part split zips (Task_1.zip.001-014 + Task_2.zip.001-007, ~21.8 GB). After download, reassemble with
cat Task_1.zip.* > Task_1.zipthen extract with 7-Zip. The Zenodo files are marked CC BY 4.0. Check any separate challenge rules before entering a competition.
Access information and download
- CLI
- Python
# Read-only preflight
eyehub download mario --data-dir ./data --dry-run --json
# Download, only when preflight reports supported behavior
eyehub download mario --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('mario')
print(preflight_dataset(ds, './data')) # no download
Upstream page: zenodo.org/records
Source-term evidence: zenodo.org/records
Loader status
This catalog record provides metadata and access instructions, but it does not yet include a standard DatasetSample loader. Inspect the source file structure or contribute a loader before using it in a training pipeline.
Citation
- BibTeX
- Plain text
@misc{mario,
title = { MARIO: AMD-Progression Longitudinal OCT (MICCAI 2024) },
note = { Quellec G, Zeghlache R, et al., 'MARIO: Monitoring AMD Progression from OCT — MICCAI 2024 Challenge', arXiv 2506.02976. Data: Zenodo doi:10.5281/zenodo.15270469 (2025). Peer-reviewed proceedings pending },
year = { 2024 },
url = { https://zenodo.org/records/15270469 },
}
Quellec G, Zeghlache R, et al., 'MARIO: Monitoring AMD Progression from OCT — MICCAI 2024 Challenge', arXiv 2506.02976. Data: Zenodo doi:10.5281/zenodo.15270469 (2025). Peer-reviewed proceedings pending.
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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