Your browser doesn't support javascript.
loading
Data-driven synthetic MRI FLAIR artifact correction via deep neural network.
Ryu, Kanghyun; Nam, Yoonho; Gho, Sung-Min; Jang, Jinhee; Lee, Ho-Joon; Cha, Jihoon; Baek, Hye Jin; Park, Jiyong; Kim, Dong-Hyun.
Afiliação
  • Ryu K; Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
  • Nam Y; Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Republic of Korea.
  • Gho SM; MR Clinical research and Development, GE Healthcare, Seoul, Republic of Korea.
  • Jang J; Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Republic of Korea.
  • Lee HJ; Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Cha J; Department of Radiology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Republic of Korea.
  • Baek HJ; Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Park J; Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea.
  • Kim DH; Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
J Magn Reson Imaging ; 50(5): 1413-1423, 2019 11.
Article em En | MEDLINE | ID: mdl-30884007
Assuntos
Palavras-chave
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Imageamento por Ressonância Magnética / Redes Neurais de Computação / Artefatos / Aprendizado Profundo Tipo de estudo: Observational_studies / Prognostic_studies / Qualitative_research Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Magn Reson Imaging Ano de publicação: 2019 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Imageamento por Ressonância Magnética / Redes Neurais de Computação / Artefatos / Aprendizado Profundo Tipo de estudo: Observational_studies / Prognostic_studies / Qualitative_research Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: J Magn Reson Imaging Ano de publicação: 2019 Tipo de documento: Article