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A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography.
Choi, Hyewon; Kim, Hyungjin; Jin, Kwang Nam; Jeong, Yeon Joo; Chae, Kum Ju; Lee, Kyung Hee; Yong, Hwan Seok; Gil, Bomi; Lee, Hye-Jeong; Lee, Ki Yeol; Jeon, Kyung Nyeo; Yi, Jaeyoun; Seo, Sola; Ahn, Chulkyun; Lee, Joonhyung; Oh, Kyuhyup; Goo, Jin Mo.
Afiliación
  • Choi H; Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine.
  • Kim H; Department of Radiology, Seoul National University College of Medicine.
  • Jin KN; Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul.
  • Jeong YJ; Department of Radiology and Biomedical Research Institute, Pusan National University Hospital, Busan.
  • Chae KJ; Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju.
  • Lee KH; Department of Radiology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do.
  • Yong HS; Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine.
  • Gil B; Department of Radiology, College of Medicine, The Catholic University of Korea.
  • Lee HJ; Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine.
  • Lee KY; Department of Radiology, Korea University College of Medicine.
  • Jeon KN; Department of Radiology, Gyeongsang National University, Jinju, Korea.
  • Yi J; Coreline Soft Inc.
  • Seo S; Coreline Soft Inc.
  • Ahn C; ClariPi Inc.
  • Lee J; VUNO Inc.
  • Oh K; Bio Medical Research Center, Korea Testing Laboratory.
  • Goo JM; Department of Radiology, Seoul National University College of Medicine.
J Thorac Imaging ; 37(4): 253-261, 2022 Jul 01.
Article en En | MEDLINE | ID: mdl-35749623
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfisema Pulmonar / Enfisema / Aprendizaje Profundo Tipo de estudio: Guideline / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Thorac Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2022 Tipo del documento: Article
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfisema Pulmonar / Enfisema / Aprendizaje Profundo Tipo de estudio: Guideline / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Thorac Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2022 Tipo del documento: Article