CS-MRI Reconstruction Using an Improved GAN with Dilated Residual Networks and Channel Attention Mechanism.

Li, Xia; Zhang, Hui; Yang, Hao; Li, Tie-Qiang

Li, Xia; Zhang, Hui; Yang, Hao; Li, Tie-Qiang.

Afiliación

Li X; College of Information Engineering, China Jiliang University, Hangzhou 310018, China.
Zhang H; College of Information Engineering, China Jiliang University, Hangzhou 310018, China.
Yang H; College of Information Engineering, China Jiliang University, Hangzhou 310018, China.
Li TQ; Department of Clinical Science, Intervention, and Technology, Karolinska Institute, 14186 Stockholm, Sweden.

Sensors (Basel) ; 23(18)2023 Sep 06.

Article en En | MEDLINE | ID: mdl-37765747

Palabras clave

GAN; U-net; channel attention mechanism; compressed sensing MRI; dilated residual blocks

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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