Application of Artificial Intelligence in Capsule Endoscopy: Where Are We Now?.
- Author:
Youngbae HWANG
1
;
Junseok PARK
;
Yun Jeong LIM
;
Hoon Jai CHUN
Author Information
- Publication Type:Review
- Keywords: Capsule endoscopy; Deep learning; Artificial intelligence; Lesion detection
- MeSH: Artificial Intelligence*; Capsule Endoscopy*; Classification; Diagnosis; Endoscopy; Specialization
- From:Clinical Endoscopy 2018;51(6):547-551
- CountryRepublic of Korea
- Language:English
- Abstract: Unlike wired endoscopy, capsule endoscopy requires additional time for a clinical specialist to review the operation and examine the lesions. To reduce the tedious review time and increase the accuracy of medical examinations, various approaches have been reported based on artificial intelligence for computer-aided diagnosis. Recently, deep learning–based approaches have been applied to many possible areas, showing greatly improved performance, especially for image-based recognition and classification. By reviewing recent deep learning–based approaches for clinical applications, we present the current status and future direction of artificial intelligence for capsule endoscopy.
