Latent signal models: Learning compact representations of signal evolution for improved time-resolved, multi-contrast MRI.

Arefeen, Yamin; Xu, Junshen; Zhang, Molin; Dong, Zijing; Wang, Fuyixue; White, Jacob; Bilgic, Berkin; Adalsteinsson, Elfar

Arefeen, Yamin; Xu, Junshen; Zhang, Molin; Dong, Zijing; Wang, Fuyixue; White, Jacob; Bilgic, Berkin; Adalsteinsson, Elfar.

Afiliação

Arefeen Y; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Xu J; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Zhang M; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Dong Z; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA.
Wang F; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA.
White J; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Bilgic B; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA.
Adalsteinsson E; Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.

Magn Reson Med ; 90(2): 483-501, 2023 08.

Article em En | MEDLINE | ID: mdl-37093775

Assuntos

Algoritmos; Imageamento por Ressonância Magnética; Imageamento por Ressonância Magnética/métodos; Simulação por Computador; Processamento de Imagem Assistida por Computador/métodos

Palavras-chave

image reconstruction; machine learning; model-based; time-resolved MRI

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Imageamento por Ressonância Magnética Tipo de estudo: Prognostic_studies / Qualitative_research Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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