A Current and Newly Proposed Artificial Intelligence Algorithm for Reading Small Bowel Capsule Endoscopy

被引:9
|
作者
Oh, Dong Jun [1 ]
Hwang, Youngbae [2 ]
Lim, Yun Jeong [1 ]
机构
[1] Dongguk Univ, Ilsan Hosp, Coll Med, Dept Internal Med, Goyang 10326, South Korea
[2] Chungbuk Natl Univ, Dept Elect Engn, Cheongju 28644, South Korea
关键词
artificial intelligence; automatic detection; capsule endoscopy; reading software; DEVICE-ASSISTED ENTEROSCOPY; DISORDERS EUROPEAN-SOCIETY; AUTOMATIC DETECTION; IMAGES; SOFTWARE; LESIONS; PERFORMANCE; LIMITATIONS; DIAGNOSIS; QUALITY;
D O I
10.3390/diagnostics11071183
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Small bowel capsule endoscopy (SBCE) is one of the most useful methods for diagnosing small bowel mucosal lesions. However, it takes a long time to interpret the capsule images. To solve this problem, artificial intelligence (AI) algorithms for SBCE readings are being actively studied. In this article, we analyzed several studies that applied AI algorithms to SBCE readings, such as automatic lesion detection, automatic classification of bowel cleanliness, and automatic compartmentalization of small bowels. In addition to automatic lesion detection using AI algorithms, a new direction of AI algorithms related to shorter reading times and improved lesion detection accuracy should be considered. Therefore, it is necessary to develop an integrated AI algorithm composed of algorithms with various functions in order to be used in clinical practice.
引用
收藏
页数:9
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