A gastric cancer recognition algorithm on gastric pathological sections based on multistage attention‐DenseNet-Reference-Cited by-同舟云学术

A gastric cancer recognition algorithm on gastric pathological sections based on multistage attention‐DenseNet

Published:2021-03-18 Issue:10 Volume:33 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Liu Bo¹^ORCID,Zhao Yelong¹^ORCID,Yang Bin¹^ORCID,Zhao Shuangtao²,Gu Rentao³,Gahegan Mark⁴

Affiliation:

1. School of Software Engineering, Faculty of Information Technology Beijing University of Technology Beijing 100124 China

2. Department of Interventional Therapy, National Cancer Center/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021 China

3. School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing 100876 China

4. School of Computer Science The University of Auckland Auckland 1010 New Zealand

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6188

Reference25 articles.

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3. Early gastric cancer: detection and endoscopic treatment;Costamagna G;Ann Ital Chir,2012

4. Evaluation of fibergastroscopic biopsy in the diagnosis of gastric cancer: A study of 339 cases

5. Automated gastric cancer diagnosis on H&E-stained sections; ltraining a classifier on a large scale with multiple instance machine learning

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