A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development. (28th June 2021)

• Record Type: Journal Article
• Authors: Ai, Shiliang; Li, Chen; Li, Xiaoyan; Jiang, Tao; Grzegorzek, Marcin; Sun, Changhao; Rahaman, Md Mamunur; Zhang, Jinghua; Yao, Yudong; Li, Hong
• Other Names: Xia Yong Academic Editor.
• Is Part Of: BioMed research international. Volume 2021(2021)
• Publication Date: 2021-06-28
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2021/6671417
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : 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.