Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Nov;51(6):547-551.
doi: 10.5946/ce.2018.173. Epub 2018 Nov 30.

Application of Artificial Intelligence in Capsule Endoscopy: Where Are We Now?

Youngbae Hwang  1 , Junseok Park  2 , Yun Jeong Lim  3 , Hoon Jai Chun  4
Affiliations

Application of Artificial Intelligence in Capsule Endoscopy: Where Are We Now?

Youngbae Hwang et al. Clin Endosc. 2018 Nov.

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.

Keywords: Artificial intelligence; Capsule endoscopy; Deep learning; Lesion detection.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest:The authors have no financial conflicts of interest.

References

    1. Iddan G, Meron G, Glukhovsky A, Swain P. Wireless capsule endoscopy. Nature. 2000;405:417. - PubMed
    1. Fisher LR, Hasler WL. New vision in video capsule endoscopy: current status and future directions. Nat Rev Gastroenterol Hepatol. 2012;9:392–405. - PubMed
    1. Kwack WG, Lim YJ. Current status and research into overcoming limitations of capsule endoscopy. Clin Endosc. 2016;49:8–15. - PMC - PubMed
    1. Szeliski R. Computer vision: algorithms and applications. London: Springer-Verlag; 2011.
    1. Liedlgruber M, Uhl A. Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review. IEEE Rev Biomed Eng. 2011;4:73–88. - PubMed

LinkOut - more resources