Development of a Super-Resolution Scheme for Pediatric Magnetic Resonance Brain Imaging Through Convolutional Neural Networks.

Molina-Maza, Juan Manuel; Galiana-Bordera, Adrian; Jimenez, Mar; Malpica, Norberto; Torrado-Carvajal, Angel

Molina-Maza, Juan Manuel; Galiana-Bordera, Adrian; Jimenez, Mar; Malpica, Norberto; Torrado-Carvajal, Angel.

Afiliação

Molina-Maza JM; Medical Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Madrid, Spain.
Galiana-Bordera A; Medical Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Madrid, Spain.
Jimenez M; Department of Radiology, Hospital Universitario Quirónsalud, Madrid, Spain.
Malpica N; Medical Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Madrid, Spain.
Torrado-Carvajal A; Medical Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Madrid, Spain.

Front Neurosci ; 16: 830143, 2022.

Article em En | MEDLINE | ID: mdl-36389232

Palavras-chave

convolutional neural networks (CNN); deep learning (DL); magnetic resonance imaging (MRI); pediatric imaging; sedation; super-resolution (SR)

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: Front Neurosci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Espanha

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