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Impact of deep learning architectures on accelerated cardiac T1 mapping using MyoMapNet.
Amyar, Amine; Guo, Rui; Cai, Xiaoying; Assana, Salah; Chow, Kelvin; Rodriguez, Jennifer; Yankama, Tuyen; Cirillo, Julia; Pierce, Patrick; Goddu, Beth; Ngo, Long; Nezafat, Reza.
Afiliação
  • Amyar A; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Guo R; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Cai X; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Assana S; Siemens Medical Solutions USA, Inc., Boston, Massachusetts, USA.
  • Chow K; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Rodriguez J; Siemens Medical Solutions USA, Inc., Chicago, Illinois, USA.
  • Yankama T; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Cirillo J; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Pierce P; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Goddu B; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Ngo L; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
  • Nezafat R; Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
NMR Biomed ; 35(11): e4794, 2022 11.
Article em En | MEDLINE | ID: mdl-35767308
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Interpretação de Imagem Assistida por Computador / Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: NMR Biomed Assunto da revista: DIAGNOSTICO POR IMAGEM / MEDICINA NUCLEAR Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Interpretação de Imagem Assistida por Computador / Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: NMR Biomed Assunto da revista: DIAGNOSTICO POR IMAGEM / MEDICINA NUCLEAR Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos