Learning to deep learning: statistics and a paradigm test in selecting a UNet architecture to enhance MRI.

Sharma, Rishabh; Tsiamyrtzis, Panagiotis; Webb, Andrew G; Leiss, Ernst L; Tsekos, Nikolaos V

Sharma, Rishabh; Tsiamyrtzis, Panagiotis; Webb, Andrew G; Leiss, Ernst L; Tsekos, Nikolaos V.

Afiliación

Sharma R; Medical Robotics and Imaging Lab, Department of Computer Science, 501, Philip G. Hoffman Hall, University of Houston, 4800 Calhoun Road, Houston, TX, 77204, USA.
Tsiamyrtzis P; Department of Mechanical Engineering, Politecnico Di Milano, Milan, Italy.
Webb AG; Department of Statistics, Athens University of Economics and Business, Athens, Greece.
Leiss EL; C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Tsekos NV; Department of Computer Science, University of Houston, Houston, TX, USA.

MAGMA ; 2023 Nov 21.

Article en En | MEDLINE | ID: mdl-37989921

Palabras clave

Deep learning; Enhance; Mixed effects modeling; Statistical significance; UNet; Undersampled

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: MAGMA Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

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