Deep-Learning-Based Preprocessing for Quantitative Myocardial Perfusion MRI.

Scannell, Cian M; Veta, Mitko; Villa, Adriana D M; Sammut, Eva C; Lee, Jack; Breeuwer, Marcel; Chiribiri, Amedeo

Scannell, Cian M; Veta, Mitko; Villa, Adriana D M; Sammut, Eva C; Lee, Jack; Breeuwer, Marcel; Chiribiri, Amedeo.

Afiliação

Scannell CM; School of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Veta M; Alan Turing Institute London, UK.
Villa ADM; Department of Biomedical Engineering, Medical Image Analysis group, Eindhoven University of Technology, Eindhoven, The Netherlands.
Sammut EC; School of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Lee J; School of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Breeuwer M; Bristol Heart Institute and Translational Biomedical Research Centre, Faculty of Health Science, University of Bristol, UK.
Chiribiri A; School of Biomedical Engineering and Imaging Sciences, King's College London, UK.

J Magn Reson Imaging ; 51(6): 1689-1696, 2020 06.

Article em En | MEDLINE | ID: mdl-31710769

Assuntos

Aprendizado Profundo; Humanos; Processamento de Imagem Assistida por Computador; Imageamento por Ressonância Magnética; Perfusão; Estudos Retrospectivos

Palavras-chave

automated image analysis; convolutional neural networks; machine learning; quantitative myocardial perfusion

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Guideline / Observational_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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