Using Stain Decomposition for Nucleus Segmentation on Multisource HE Slide Images

Hung Chun Hsu, Hung Wen Tsai, Maria Gabrani, Pau Choo Chung, Antonio Foncubierta Rodriguez, Yu Ting Wu

研究成果: Conference contribution

3 引文 斯高帕斯(Scopus)

摘要

The deep learning technique is widely used for whole slide image (WSI) analysis due to its speed and relatively objective results. Nucleus instance segmentation, in which the nuclei in the WSI are individually identified, can provide many useful parameters to assist and accelerate the diagnosis process for pathologists. Hematoxylin and eosin stain (HE stain) is commonly used on pathology tissue slides to observe the behavior and structure information of cells. However, the color-oriented features of the nuclei vary widely depending on the dye and staining protocol employed and also the scanning system used to obtain the digital WSIs. Accordingly, the proposed lightweight network module attached to the front of an arbitrary network can provide a more robust segmentation performance irrespective of staining protocols employed and scanning circumstances. Notably, the proposed module improves the performance for unseen color-oriented features and thus can benefit the realworld applications, where the WSIs may be collected from multiple hospitals and laboratories.

原文English
主出版物標題2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728190488
DOIs
出版狀態Published - 2021
事件2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Orlando, United States
持續時間: 2021 12月 52021 12月 7

出版系列

名字2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings

Conference

Conference2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021
國家/地區United States
城市Orlando
期間21-12-0521-12-07

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦科學應用
  • 決策科學(雜項)
  • 安全、風險、可靠性和品質
  • 控制和優化

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