Preparation of image databases for artificial intelligence algorithm development in gastrointestinal endoscopy
양창봉, 김상훈, 임윤정,
소속 상세정보
양창봉 ( Yang Chang-Bong )
Dongguk University College of Medicine Dongguk University Ilsan Hospital Department of Internal Medicine
김상훈 ( Kim Sang-Hoon )
Dongguk University College of Medicine Dongguk University Ilsan Hospital Department of Internal Medicine
임윤정 ( Lim Yun-Jeong )
Dongguk University College of Medicine Dongguk University Ilsan Hospital Department of Internal Medicine
Abstract
Over the past decade, technological advances in deep learning have led to the introduction of artificial intelligence (AI) in medical imaging. The most commonly used structure in image recognition is the convolutional neural network, which mimics the action of the human visual cortex. The applications of AI in gastrointestinal endoscopy are diverse. Computer-aided diagnosis has achieved remarkable outcomes with recent improvements in machine-learning techniques and advances in computer performance. Despite some hurdles, the implementation of AI-assisted clinical practice is expected to aid endoscopists in real-time decision-making. In this summary, we reviewed state-of-the-art AI in the field of gastrointestinal endoscopy and offered a practical guide for building a learning image dataset for algorithm development.
키워드
Artificial intelligence; Deep learning; Gastrointestinal endoscopy
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