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
- Laser & Optoelectronics Progress
- Vol. 57, Issue 2, 21014 (2020)
Fig. 1. Basic unit of residual learning
Fig. 2. Channel-attention mechanism block
Fig. 3. Network structure based on deep residual channel attention. (a) Basic unit; (b) network structure
Fig. 4. Loss curve of each method on lung CT dataset
Fig. 5. Loss curve of each method on prostate MRI dataset
Fig. 6. Comparison of rendering of images with super-resolution magnification of 2 under each super resolution method. (a) Lung tip tra CT; (b) lung leaf tra CT; (c) prostateX-0061 T2_tse_tra MRI; (d) prostateX-0082 T2_tse_tra MRI
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Table 1. Experimental environment parameters
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Table 2. Objective evaluation of each super-resolution method
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