Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-weighted FS sequence.

Shanbhogue, Krishna; Tong, Angela; Smereka, Paul; Nickel, Dominik; Arberet, Simon; Anthopolos, Rebecca; Chandarana, Hersh

Shanbhogue, Krishna; Tong, Angela; Smereka, Paul; Nickel, Dominik; Arberet, Simon; Anthopolos, Rebecca; Chandarana, Hersh.

Afiliação

Shanbhogue K; Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA. Krishna.shanbhogue@nyulangone.org.
Tong A; Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA.
Smereka P; Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA.
Nickel D; Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052, Erlangen, Germany.
Arberet S; Digital Technology & Innovation, Siemens Medical Solutions USA, Inc., Princeton, NJ, USA.
Anthopolos R; Department of Biostatistics, NYU Langone School of Medicine, New York, NY, 10016, USA.
Chandarana H; Department of Radiology, NYU Langone Health, 660 1st Avenue, 3rd Floor, New York, NY, 10016, USA.

Eur Radiol ; 31(11): 8447-8457, 2021 Nov.

Article em En | MEDLINE | ID: mdl-33961086

Assuntos

Aprendizado Profundo; Artefatos; Humanos; Processamento de Imagem Assistida por Computador; Fígado/diagnóstico por imagem; Imageamento por Ressonância Magnética

Palavras-chave

Artificial intelligence; Deep learning; Liver; Magnetic resonance imaging

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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