Deep Convolutional Neural Network for Inverse Problems in Imaging

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    Zhenxing Huang, Zixiang Chen, Guotao Quan, Yanfeng Du, Yongfeng Yang, Xin Liu, Hairong Zheng, Dong Liang, Zhanli Hu · 2022 · IEEE Transactions on Radiation and Plasma Medical Sciences
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    Yuhang Liu, Yi Liu, Pengcheng Zhang, Rongbiao Yan, Lei Wang, Wenting Liu, Zhiguo Gui · 2022 · NDT & E International
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34. Material Decomposition in Spectral CT Using Deep Learning: A Sim2Real Transfer Approach
    Juan Abascal, Nicolas Ducros, Valeriya Pronina, Simon Rit, Pierre‐Antoine Rodesch, Thomas Broussaud, Suzanne Bussod, Philippe Douek, Andreas Hauptmann, Simon Arridge et al. · 2021 · IEEE Access
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    Rajeev Yasarla, Jeya Maria Jose Valanarasu, Vishal M. Patel · 2020 · IEEE Journal of Selected Topics in Signal Processing
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    Fengqin Zhang, Minghui Zhang, Binjie Qin, Yi Zhang, Zichen Xu, Dong Liang, Qiegen Liu · 2020 · IEEE Transactions on Radiation and Plasma Medical Sciences
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    Yongwan Lim, Yannick Bliesener, Shrikanth Shri Narayanan · 2020 · Magnetic Resonance in Medicine
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    Pei Peng, Shirin Jalali, Xin Yuan · 2020 · IEEE Journal on Selected Areas in Information Theory
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    Jianjun Liu, Dunbin Shen, Zebin Wu, Liang Xiao, Jun Sun, Hong Yan · 2022 · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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