Autonomous Retinal Vein Cannulation Data and Code
Surgical-microscope and intraoperative-OCT data for autonomous robotic retinal-vein cannulation in ex vivo porcine eyes.
At a glance
| Field | Value |
|---|---|
| Short name | dryad_retinal_vein_cannulation |
| Full name | Autonomous Retinal Vein Cannulation Data and Code |
| Primary category | multimodal |
| Contained modalities | surgical_video, oct |
| Tasks | classification, navigation, surgical_workflow |
| Samples | 26 |
| Classes | Not reported (Not reported) |
| Splits | all |
| Size | 7.511 GB |
| Source-stated terms | CC0 1.0 |
| 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 | Dryad |
| Availability | available (checked 2026-07-21) |
| Acquisition support | standard_platform_supported |
| Legacy sample-loader status | Metadata and access only |
Notes
Experiments used 20 static and six motion-simulated ex vivo porcine eyes. The large release contains model-training data and code.
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download dryad_retinal_vein_cannulation --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download dryad_retinal_vein_cannulation --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('dryad_retinal_vein_cannulation')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: https://doi.org/10.5061/dryad.3ffbg79zd
Source-term evidence: https://doi.org/10.5061/dryad.3ffbg79zd
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{dryad_retinal_vein_cannulation,
title = { Autonomous Retinal Vein Cannulation Data and Code },
note = { Zhang P, Gehlbach P, Taylor R, Iordachita I, Kobilarov M. Data and code from: Deep learning-based autonomous retinal vein cannulation in ex vivo porcine eyes. Dryad. 2025. doi:10.5061/dryad.3ffbg79zd },
year = { 2025 },
url = { https://doi.org/10.5061/dryad.3ffbg79zd },
}
Zhang P, Gehlbach P, Taylor R, Iordachita I, Kobilarov M. Data and code from: Deep learning-based autonomous retinal vein cannulation in ex vivo porcine eyes. Dryad. 2025. doi:10.5061/dryad.3ffbg79zd
Source-stated terms
- Raw source string: CC0 1.0
- 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.
Related datasets with shared modalities
- lmod_plus: LMOD+ Multimodal Ophthalmology Benchmark (32,633 records,
unknown) - dryad_subretinal_robot: Head-Mounted Robot Subretinal Injection Dataset (count not reported records,
cc0) - syn_oct: SYN-OCT Synthetic Glaucoma OCT Dataset (200,000 records,
cc-by) - ophora: Ophora-160K: Ophthalmic Surgical Video Instruction Dataset (160,185 records,
unknown) - eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 records,
unknown) - kermany_oct: Kermany OCT 2018: Retinal OCT Image Classification (84,484 records,
cc-by) - multieye: MultiEYE: OCT-Enhanced Fundus Multi-Disease Benchmark (58,036 records,
mit) - harvard_fairvision: Harvard-FairVision (AMD + DR + Glaucoma, paired SLO + OCT) (30,000 records,
cc-by-nc-nd)