MR image reconstruction using deep learning: evaluation of network structure and loss functions.

Ghodrati, Vahid; Shao, Jiaxin; Bydder, Mark; Zhou, Ziwu; Yin, Wotao; Nguyen, Kim-Lien; Yang, Yingli; Hu, Peng

Ghodrati, Vahid; Shao, Jiaxin; Bydder, Mark; Zhou, Ziwu; Yin, Wotao; Nguyen, Kim-Lien; Yang, Yingli; Hu, Peng.

Afiliación

Ghodrati V; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
Shao J; Biomedical Physics Inter-Departmental Graduate Program, University of California, Los Angeles, CA, USA.
Bydder M; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
Zhou Z; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
Yin W; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
Nguyen KL; Department of Bioengineering, University of California, Los Angeles, CA, USA.
Yang Y; Department of Mathematics, University of California, Los Angeles, CA, USA.
Hu P; Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.

Quant Imaging Med Surg ; 9(9): 1516-1527, 2019 Sep.

Article en En | MEDLINE | ID: mdl-31667138

Palabras clave

Magnetic resonance imaging; cardiac image reconstruction; convolutional Unet; deep learning; perceptual loss function; residual neural network

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Qualitative_research Idioma: En Revista: Quant Imaging Med Surg Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: China

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google