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A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development
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 gast...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8257332/ https://www.ncbi.nlm.nih.gov/pubmed/34258279 http://dx.doi.org/10.1155/2021/6671417 |
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author | Ai, Shiliang Li, Chen Li, Xiaoyan Jiang, Tao Grzegorzek, Marcin Sun, Changhao Rahaman, Md Mamunur Zhang, Jinghua Yao, Yudong Li, Hong |
author_facet | Ai, Shiliang Li, Chen Li, Xiaoyan Jiang, Tao Grzegorzek, Marcin Sun, Changhao Rahaman, Md Mamunur Zhang, Jinghua Yao, Yudong Li, Hong |
author_sort | Ai, Shiliang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8257332 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-82573322021-07-12 A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development Ai, Shiliang Li, Chen Li, Xiaoyan Jiang, Tao Grzegorzek, Marcin Sun, Changhao Rahaman, Md Mamunur Zhang, Jinghua Yao, Yudong Li, Hong Biomed Res Int Review Article 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. Hindawi 2021-06-26 /pmc/articles/PMC8257332/ /pubmed/34258279 http://dx.doi.org/10.1155/2021/6671417 Text en Copyright © 2021 Shiliang Ai et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Ai, Shiliang Li, Chen Li, Xiaoyan Jiang, Tao Grzegorzek, Marcin Sun, Changhao Rahaman, Md Mamunur Zhang, Jinghua Yao, Yudong Li, Hong A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development |
title | A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development |
title_full | A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development |
title_fullStr | A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development |
title_full_unstemmed | A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development |
title_short | A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development |
title_sort | state-of-the-art review for gastric histopathology image analysis approaches and future development |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8257332/ https://www.ncbi.nlm.nih.gov/pubmed/34258279 http://dx.doi.org/10.1155/2021/6671417 |
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