Application of Artificial Intelligence in Capsule Endoscopy: Where Are We Now?
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초록
Unlike wired endoscopy, capsule endoscopy requires additional time for a clinical specialist to review the operation and examine thelesions. To reduce the tedious review time and increase the accuracy of medical examinations, various approaches have been reportedbased on artificial intelligence for computer-aided diagnosis. Recently, deep learning–based approaches have been applied to manypossible areas, showing greatly improved performance, especially for image-based recognition and classification. By reviewing recentdeep learning–based approaches for clinical applications, we present the current status and future direction of artificial intelligence forcapsule endoscopy.
Abstract
Unlike wired endoscopy, capsule endoscopy requires additional time for a clinical specialist to review the operation and examine thelesions. To reduce the tedious review time and increase the accuracy of medical examinations, various approaches have been reportedbased on artificial intelligence for computer-aided diagnosis. Recently, deep learning–based approaches have been applied to manypossible areas, showing greatly improved performance, especially for image-based recognition and classification. By reviewing recentdeep learning–based approaches for clinical applications, we present the current status and future direction of artificial intelligence forcapsule endoscopy.
참고문헌 (41)
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