{
 "id": "MedOtter/PROSTATEx-Seg-HiRes",
 "owner": "MedOtter",
 "name": "PROSTATEx-Seg-HiRes",
 "downloads": 64,
 "likes": 0,
 "last_modified": "2026-08-25T20:08:17.000Z",
 "stated_licence": "cc-by-3.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "image-segmentation"
 ],
 "citation": "@article{meyer2021anisotropic,\n  title   = {Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI},\n  author  = {Meyer, Anneke and Chlebus, Grzegorz and Rak, Marko and Schindele, Daniel and\n             Schostak, Martin and van Ginneken, Bram and Schenk, Andrea and Meine, Hans and\n             Hahn, Horst K. and Schreiber, Andreas and Hansen, Christian},\n  journal = {Computer Methods and Programs in Biomedicine},\n  volume  = {200}, pages = {105821}, year = {2021},\n  doi     = {10.1016/j.cmpb.2020.105821}\n}\n\n@misc{schindele2020hires,\n  title     = {High Resolution Prostate Segmentations for the ProstateX-Challenge},\n  author    = {Schindele, Daniel and Meyer, Anneke and Von Reibnitz, Donata F. and\n               Kiesswetter, Verena and Schostak, Martin and Rak, Marko and Hansen, Christian},\n  publisher = {The Cancer Imaging Archive}, year = {2020},\n  doi       = {10.7937/TCIA.2019.DEG7ZG1U}\n}",
 "signal": "permissive",
 "reason": "The declared licence (cc-by-3.0) is classified as permissive.",
 "revision": "46fde9ef292db6d61b11765042155d38245b8a7e",
 "stated_evidence": "https://huggingface.co/datasets/MedOtter/PROSTATEx-Seg-HiRes/blob/46fde9ef292db6d61b11765042155d38245b8a7e/README.md",
 "file_evidence": "https://huggingface.co/datasets/MedOtter/PROSTATEx-Seg-HiRes/tree/46fde9ef292db6d61b11765042155d38245b8a7e",
 "card_nc": false
}