Medical-Image Super-Resolution Reconstruction Method Based on Residual Channel Attention Network

Liu Kewen; Ma Yuan; Xiong Hongxia; Yan Zejun; Zhou Zhijun; Liu Chaoyang; Fang Panpan; Li Xiaojun; Chen Yalei

doi:10.3788/LOP57.021014

Journals >Laser & Optoelectronics Progress >Volume 57 >Issue 2 >Page 21014 > Article

Laser & Optoelectronics Progress
Vol. 57, Issue 2, 21014 (2020)

Medical-Image Super-Resolution Reconstruction Method Based on Residual Channel Attention Network

Liu Kewen^1、2, Ma Yuan^1、2, Xiong Hongxia^3、*, Yan Zejun⁴, Zhou Zhijun⁵, Liu Chaoyang⁶, Fang Panpan^1、2, Li Xiaojun^1、2, and Chen Yalei^1、2

Author Affiliations

¹School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China

²Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, Wuhan University of Technology, Wuhan, Hubei 430070, China

³School of Civil Engineering & Architecture, Wuhan University of Technology, Wuhan, Hubei 430070, China

⁴Department of Urology, Ningbo First Hospital, Key Laboratory of Translational Medicine of Urological Diseases in Ningbo, Ningbo, Zhejiang 315010, China

⁵Department of Urology, the First People''s Hospital of Tianmen, Tianmen, Hubei 431700, China

⁶State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China

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DOI: 10.3788/LOP57.021014 Cite this Article Set citation alerts

Liu Kewen, Ma Yuan, Xiong Hongxia, Yan Zejun, Zhou Zhijun, Liu Chaoyang, Fang Panpan, Li Xiaojun, Chen Yalei. Medical-Image Super-Resolution Reconstruction Method Based on Residual Channel Attention Network[J]. Laser & Optoelectronics Progress, 2020, 57(2): 21014 Copy Citation Text

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