Weakly supervised cell instance segmentation by propagating from detection response

Kazuya Nishimura, Dai Fei Elmer Ker, Ryoma Bise

研究成果: 著書/レポートタイプへの貢献会議での発言

抜粋

Cell shape analysis is important in biomedical research. Deep learning methods may perform to segment individual cells if they use sufficient training data that the boundary of each cell is annotated. However, it is very time-consuming for preparing such detailed annotation for many cell culture conditions. In this paper, we propose a weakly supervised method that can segment individual cell regions who touch each other with unclear boundaries in dense conditions without the training data for cell regions. We demonstrated the efficacy of our method using several data-set including multiple cell types captured by several types of microscopy. Our method achieved the highest accuracy compared with several conventional methods. In addition, we demonstrated that our method can perform without any annotation by using fluorescence images that cell nuclear were stained as training data. Code is publicly available in https://github.com/naivete5656/WSISPDR.

元の言語英語
ホスト出版物のタイトルMedical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings
編集者Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou
出版者Springer
ページ649-657
ページ数9
ISBN(印刷物)9783030322380
DOI
出版物ステータス出版済み - 1 1 2019
イベント22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, 中国
継続期間: 10 13 201910 17 2019

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11764 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

会議

会議22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019
中国
Shenzhen
期間10/13/1910/17/19

    フィンガープリント

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

これを引用

Nishimura, K., Ker, D. F. E., & Bise, R. (2019). Weakly supervised cell instance segmentation by propagating from detection response. : D. Shen, P-T. Yap, T. Liu, T. M. Peters, A. Khan, L. H. Staib, C. Essert, ... S. Zhou (版), Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings (pp. 649-657). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 11764 LNCS). Springer. https://doi.org/10.1007/978-3-030-32239-7_72