CASIA OpenIR  > 中国科学院分子影像重点实验室
A Computational Prediction Method Based on Modified U-Net for Cell Distribution in Tumor Microenvironment
Bian, Chang1,2; Wang, Yu1,2; An, Yu1,3; Wang, Hanfan1,4; Du, Yang1,2; Tian, Jie1,2,3,4
2021-02
Conference NameSPIE Medical Imaging 2021
Conference Date2021-2-15
Conference Place线上会议
Abstract

The tumor microenvironment (TME) is the internal environment in which tumors develop and consists of tumor cells, various immune cells, and interstitial cells. Understanding TME can help predict clinical response of immunotherapy and offer guidance for therapeutic optimization. Current pathological practice utilizes multiplexed immunohistochemistry (mIHC) to make assessment of different types of cell distribution in TME. However, these staining methods are not only costly but  can also reduce the quality of the sample tissues and staining results often require professional pathologists to interpret, which can be possibly influenced by subjectivity. In this work, we propose a computational prediction method for cell distribution in TME using a modified U-Net structure, which can learn useful features from the hematoxylin and eosin (H&E) images and predict PanCK positive colon cells and tumor infiltrating lymphocytes (TILs) at cellular-level. Our created datasets contain H&E images and cellular-level segmentation labels annotated by board-certified pathologists according to the corresponding registered mIHC images. We combined U-Net and Inception block structure and created a modified U-net network which can predict PanCK positive colon cells and TILs distribution in TME,with the accuracy of 84.6% on test set. Hence, this method shows the potential to make assessment of different types of cell distribution in TME more objectively and efficiently.

Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/44325
Collection中国科学院分子影像重点实验室
Corresponding AuthorDu, Yang; Tian, Jie
Affiliation1.CAS Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
2.The University of Chinese Academy of Sciences, Beijing, 100080, China
3.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, 100191, China
4.Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi, 710126, China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Bian, Chang,Wang, Yu,An, Yu,et al. A Computational Prediction Method Based on Modified U-Net for Cell Distribution in Tumor Microenvironment[C],2021.
Files in This Item: Download All
File Name/Size DocType Version Access License
SPIE.pdf(28768KB)会议论文 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Bian, Chang]'s Articles
[Wang, Yu]'s Articles
[An, Yu]'s Articles
Baidu academic
Similar articles in Baidu academic
[Bian, Chang]'s Articles
[Wang, Yu]'s Articles
[An, Yu]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Bian, Chang]'s Articles
[Wang, Yu]'s Articles
[An, Yu]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: SPIE.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.