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Deep Learning for Quantitative Cardiac MRI.
Tao, Qian; Lelieveldt, Boudewijn P F; van der Geest, Rob J.
Afiliação
  • Tao Q; Department of Radiology, Division of Image Processing, Leiden University Medical Center, Albinusdreef 2, Leiden, Zuidholland 2333ZA, The Netherlands.
  • Lelieveldt BPF; Department of Radiology, Division of Image Processing, Leiden University Medical Center, Albinusdreef 2, Leiden, Zuidholland 2333ZA, The Netherlands.
  • van der Geest RJ; Department of Radiology, Division of Image Processing, Leiden University Medical Center, Albinusdreef 2, Leiden, Zuidholland 2333ZA, The Netherlands.
AJR Am J Roentgenol ; 214(3): 529-535, 2020 03.
Article em En | MEDLINE | ID: mdl-31670597
ABSTRACT
OBJECTIVE. The recent advancement of deep learning techniques has profoundly impacted research on quantitative cardiac MRI analysis. The purpose of this article is to introduce the concept of deep learning, review its current applications on quantitative cardiac MRI, and discuss its limitations and challenges. CONCLUSION. Deep learning has shown state-of-the-art performance on quantitative analysis of multiple cardiac MRI sequences and holds great promise for future use in clinical practice and scientific research.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador / Doenças Cardiovasculares / Aprendizado Profundo Limite: Humans Idioma: En Revista: AJR Am J Roentgenol Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador / Doenças Cardiovasculares / Aprendizado Profundo Limite: Humans Idioma: En Revista: AJR Am J Roentgenol Ano de publicação: 2020 Tipo de documento: Article