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A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development

文献类型：期刊论文

作者Ai, Shiliang5; Li, Chen5; Li, Xiaoyan1; Jiang, Tao6; Grzegorzek, Marcin2; Sun, Changhao2,3,5; Rahaman, Md Mamunur5; Zhang, Jinghua2,5; Yao, Yudong4; Li, Hong5
刊名BioMed Research International
出版日期2021
卷号2021页码:1-19
ISSN号2314-6133
产权排序5
英文摘要

Gastric cancer is a common and deadly cancer in the world. The gold standard for the detection of gastric cancer is the histological examination by pathologists, where Gastric Histopathological Image Analysis (GHIA) contributes significant diagnostic information. The histopathological images of gastric cancer contain sufficient characterization information, which plays a crucial role in the diagnosis and treatment of gastric cancer. In order to improve the accuracy and objectivity of GHIA, Computer-Aided Diagnosis (CAD) has been widely used in histological image analysis of gastric cancer. In this review, the CAD technique on pathological images of gastric cancer is summarized. Firstly, the paper summarizes the image preprocessing methods, then introduces the methods of feature extraction, and then generalizes the existing segmentation and classification techniques. Finally, these techniques are systematically introduced and analyzed for the convenience of future researchers.

WOS关键词COMPUTER-AIDED DIAGNOSIS ; WHOLE SLIDE IMAGES ; CANCER ; CLASSIFICATION ; SEGMENTATION ; CONVOLUTION ; PROSTATE
资助项目National Natural Science Foundation of China[61806047] ; Fundamental Research Funds for the Central Universities[N2019003] ; China Scholarship Council[2018GBJ001757]
WOS研究方向Biotechnology & Applied Microbiology ; Research & Experimental Medicine
语种英语
WOS记录号WOS:000675285700001
资助机构National Natural Science Foundation of China (No. 61806047) ; Fundamental Research Funds for the Central Universities (No. N2019003) ; China Scholarship Council (2018GBJ001757)
源URL[http://ir.sia.cn/handle/173321/29355]  
专题沈阳自动化研究所_其他
通讯作者Li, Chen; Li, Xiaoyan
作者单位1.Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, 110042, China
2.Institute of Medical Informatics, University of Luebeck, Luebeck, Germany
3.Shenyang Institute of Automation, Chinese Academy of Sciences110169, China
4.Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
5.Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China
6.Control Engineering College, Chengdu University of Information Technology, Chengdu, 610103, China
推荐引用方式
GB/T 7714		 Ai, Shiliang,Li, Chen,Li, Xiaoyan,et al. A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development[J]. BioMed Research International,2021,2021:1-19.
APA Ai, Shiliang.,Li, Chen.,Li, Xiaoyan.,Jiang, Tao.,Grzegorzek, Marcin.,...&Li, Hong.(2021).A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development.BioMed Research International,2021,1-19.
MLA Ai, Shiliang,et al."A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development".BioMed Research International 2021(2021):1-19.

入库方式： OAI收割

来源：沈阳自动化研究所

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