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Improved classification and localization approach to small bowel capsule endoscopy using convolutional neural network.

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第一作者： Yunseob,Hwang

第一单位： Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Korea.;Postech-Catholic Biomedical Engineering Institute, Pohang University of Science and Technology (POSTECH), Pohang, Korea.

作者： Yunseob,Hwang ^[1] ; Han Hee,Lee ^[2] ; Chunghyun,Park ^[3] ; Bayu Adhi,Tama ^[3] ; Jin Su,Kim ^[4] ; Dae Young,Cheung ^[4] ; Woo Chul,Chung ^[4] ; Young-Seok,Cho ^[4] ; Kang-Moon,Lee ^[4] ; Myung-Gyu,Choi ^[4] ; Seungchul,Lee ^[5] ; Bo-In,Lee ^[4]

作者单位： Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Korea.;Postech-Catholic Biomedical Engineering Institute, Pohang University of Science and Technology (POSTECH), Pohang, Korea. ^[1] Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.;Postech-Catholic Biomedical Engineering Institute, College of Medicine, The Catholic University of Korea, Seoul, Korea. ^[2] Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Korea. ^[3] Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea. ^[4] Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Korea.;Postech-Catholic Biomedical Engineering Institute, Pohang University of Science and Technology (POSTECH), Pohang, Korea.;Graduate School of Artificial Intelligence, Pohang University of Science and Technology (POSTECH), Pohang, Korea. ^[5]

关键词 artificial intelligence capsule endoscopy computer-assisted diagnosis deep learning gastrointestinal hemorrhage

医学主题词人工智能(Artificial Intelligence);胶囊内窥镜检查(Capsule Endoscopy);人类(Humans);小肠(Intestine, Small)

DOI 10.1111/den.13787

PMID 32640059

发布时间 2021-07-28

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