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nnU-Net-BPR-annotations

imported

data/nnu-net-bpr-annotations

Code accompanying this dataset: Krishnaswamy, D., Bontempi, D., Clunie, D., Aerts, H. & Fedorov, A. AI-derived annotations for the NLST and NSCLC-Radiomics computed tomography imaging collections.…

Machine-generated from the listed sources and not yet reviewed by a human.

nnU-Net-BPR-annotations project image
GitHub preview card for ImagingDataCommons/nnU-Net-BPR-annotations. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Data & Standards
Subcategory
unknown
License
BSD-3-Clause(osi)
Status
dormant
Maturity
deployed
Organization
ImagingDataCommons
Country
unknown
Homepage
doi.org/10.5281/zenodo.7473970
Repository
github.com/ImagingDataCommons/nnU-Net-BPR-annotations
Documentation
unknown
Tags
colaboratory · deep-learning · dicom · medical-image-processing · medical-imaging · reproducible-research
Regulatory
unknown
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sources
  1. api.github.com/repos/ImagingDataCommons/nnU-Net-BPR-annotations
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2024-01-22, 8 stars, license reported as BSD-3-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/12.json→ .entries["nnu-net-bpr-annotations"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.