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Development and validation of an ensemble artificial intelligence model for comprehensive imaging quality check to classify body parts and contrast enhancement.
Na, Seongwon; Sung, Yu Sub; Ko, Yousun; Shin, Youngbin; Lee, Junghyun; Ha, Jiyeon; Ham, Su Jung; Yoon, Kyoungro; Kim, Kyung Won.
  • Na S; Department of Computer Science and Engineering, Konkuk University, Seoul, Korea.
  • Sung YS; Clinical Research Center, Asan Medical Center, Seoul, Korea.
  • Ko Y; Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul, Korea.
  • Shin Y; Biomedical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea.
  • Lee J; Biomedical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea.
  • Ha J; Department of Medical Science, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Ham SJ; Department of Radiology, Hallym University College of Medicine, Kangdong Seong-Sim Hospital, Seoul, Korea.
  • Yoon K; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea.
  • Kim KW; Department of Smart ICT Convergence Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-Gu, Seoul, Republic of Korea. yoonk@konkuk.ac.kr.
BMC Med Imaging ; 22(1): 87, 2022 05 13.
Article en En | MEDLINE | ID: mdl-35562705
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Aprendizaje Profundo Tipo de estudio: Observational_studies Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Aprendizaje Profundo Tipo de estudio: Observational_studies Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article