基于无线胶囊内窥镜图像的胃肠道病变智能检测方法综述

doi:10.3969/j.issn.0258-8021.2024.05.008

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Abstract Wireless capsule endoscopy (WCE) is a non-invasive and painless method for gastrointestinal (GI) tract examination, but it produce tens of thousands of images during the examination, which may only contain a few abnormal images. The review work highly relies on the clinical experience of physicians, which is time-consuming and easily cause false detection and/or missed detection. Therefore, exploring automated detection methods of WCE abnormal images to aid to clinical diagnosis with high accuracy and efficiency has become a research hotspot in this field. This paper reviewed recent researches on intelligently detecting GI lesions on WCE images. We first introduced the basic principles and evaluation metrics of intelligent detection methods, and then outlined the researches on intelligent detection methods of WCE abnormal images in recent years from the perspectives of traditional machine learning and deep learning algorithms, and summarized the advantages and shortcomings of the reported methods. Finally, this paper discussed and concluded the current challenges and possible future research directions in automatic lesion classification of WCE.

Key words： intelligent detection gastrointestinal tract lesion wireless capsule endoscopy deep learning machine learning

Received: 17 May 2023

PACS:

R318

Corresponding Authors: ^*E-mail: lilh@hdu.edu.cn

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	Fan Shanhui
	Wei Shangguang
	Wei Kaihua
	Fan Yihong
	Lv Bin
	Fan Kai
	Li Lihua

Cite this article:

Fan Shanhui,Wei Shangguang,Wei Kaihua, et al. A Review on Intelligent Detection Methods of Gastrointestinal Tract Lesions Based on WirelessCapsule Endoscopy Images[J]. Chinese Journal of Biomedical Engineering, 2024, 43(5): 596-608.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2024.05.008 OR http://cjbme.csbme.org/EN/Y2024/V43/I5/596

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