Data Structure ?
1.93G
Data Structure ?
*The above analysis is the result extracted and analyzed by the system, and the specific actual data shall prevail.
README.md
19種類の異なる組織タイプにわたる網羅的な核ラベルを持つ半自動生成の核インスタンスセグメンテーションと分類データセット。このデータセットは481の視野で構成されており、そのうち312は複数のデータソースからの異なる倍率の2万枚以上の全スライド画像からランダムにサンプリングされたものです。全体でこのデータセットには205,343個のラベル付き核が含まれており、それぞれにインスタンスセグメンテーションマスクがあります。PanNukeで訓練されたモデルは、全スライド画像の組織タイプセグメンテーションに役立ち、新しい組織にも汎化できます。PanNukeは、最初に成功した半自動生成データセットの1つを示しています。
データ形式
網羅的に注釈付けされたPanNukeデータセットからのサンプルで、核インスタンスセグメンテーションと分類のための19種類の組織タイプの画像パッチが含まれています（赤色：腫瘍性；緑色：炎症性；濃い青色：結合組織；黄色：死細胞；オレンジ色：上皮）
核タイプの統計
組織ごとのクラス分布の比較グラフ。括弧内の数字は、そのカテゴリまたは組織タイプ内の核の総数を表します。
引用
@inproceedings{gamper2019pannuke,
title={PanNuke: 核インスタンスセグメンテーションと分類のためのオープンな汎がん組織学データセット},
author={Gamper, Jevgenij と Koohbanani, Navid Alemi と Benet, Ksenija と Khuram, Ali と Rajpoot, Nasir},
booktitle={ヨーロッパデジタル病理学大会},
pages={11--19},
year={2019},
organization={Springer}
}
@article{gamper2020pannuke,
title={PanNukeデータセットの拡張、洞察とベースライン},
author={Gamper, Jevgenij と Koohbanani, Navid Alemi と Graham, Simon と Jahanifar, Mostafa と Khurram, Syed Ali と Azam, Ayesha と Hewitt, Katherine と Rajpoot, Nasir},
journal={arXiv事前印刷 arXiv:2003.10778},
year={2020}
}
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