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Super-resolution and denoising of 4D-Flow MRI using physics-Informed deep neural nets.
Fathi, Mojtaba F; Perez-Raya, Isaac; Baghaie, Ahmadreza; Berg, Philipp; Janiga, Gabor; Arzani, Amirhossein; D'Souza, Roshan M.
Afiliação
  • Fathi MF; Dept. of Mechanical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
  • Perez-Raya I; Dept. of Mechanical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
  • Baghaie A; Dept. of Electrical and Computer Engineering, New York Institute of Technology, Long Island, NY, USA.
  • Berg P; Lab. of Fluid Dynamics and Technical Flows, University of Magdeburg, Germany; Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany.
  • Janiga G; Lab. of Fluid Dynamics and Technical Flows, University of Magdeburg, Germany; Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany.
  • Arzani A; Dept. of Mechanical Engineering, Northern Arizona University, Flagstaff, AZ, USA.
  • D'Souza RM; Dept. of Mechanical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA. Electronic address: dsouza@uwm.edu.
Comput Methods Programs Biomed ; 197: 105729, 2020 Dec.
Article em En | MEDLINE | ID: mdl-33007592

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Imageamento Tridimensional Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Comput Methods Programs Biomed Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Imageamento Tridimensional Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Comput Methods Programs Biomed Ano de publicação: 2020 Tipo de documento: Article