TY - JOUR
T1 - A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development
AU - Ai, Shiliang
AU - Li, Chen
AU - Li, Xiaoyan
AU - Jiang, Tao
AU - Grzegorzek, Marcin
AU - Sun, Changhao
AU - Rahaman, Md Mamunur
AU - Zhang, Jinghua
AU - Yao, Yudong
AU - Li, Hong
N1 - Publisher Copyright:
© 2021 Shiliang Ai et al.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
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U2 - 10.1155/2021/6671417
DO - 10.1155/2021/6671417
M3 - Review article
C2 - 34258279
AN - SCOPUS:85110222897
SN - 2314-6133
VL - 2021
JO - BioMed Research International
JF - BioMed Research International
M1 - 6671417
ER -