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Recently, deep learning based methods appeared as a new paradigm for solving inverse problems.
Regularization of inverse problems
H. W. Engl, M. Hanke, and A. Neubauer · 1996
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Variational methods in imaging
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Image prediction for limited-angle tomography via deep learning with convolutional neural network
H Zhang, L. Li, K. Qiao, L. Wang, B. Yan, L. Li, and G. Hu · 2016
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Solving ill-posed inverse problems using iterative deep neural networks
J. Adler and O. Öktem · 2017
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Deep learning for photoacoustic tomography from sparse data
S. Antholzer, M. Haltmeier, and J. Schwab · 2017
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One network to solve them all – solving linear inverse problems using deep projection models
J.H.R. Chang, C. Li, B. Poczos, V. Kumar, and A.C. Sankaranarayanan · 2017
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Low-dose CT via convolutional neural network
H. Chen, Y. Zhang, W. Zhang, P. Liao, K. Li, J. Zhou, and G. Wang · 2017
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Deep learning-guided image reconstruction from incomplete data
B. Kelly, T. P. Matthews, and M. A. Anastasio · 2017
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Variational networks: connecting variational methods and deep learning
E. Kobler, T. Klatzer, K. Hammernik, and T. Pock · 2017
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Deep residual learning for compressed sensing mri
Dongwook Lee, Jaejun Yoo, and Jong Chul Ye · 2017
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Deep learning microscopy
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Modern regularization methods for inverse problems
M. Benning and M. Burger · 2018
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Cnn-based projected gradient descent for consistent ct image reconstruction
H. Gupta, Kyong H. Jin, H. Q. Nguyen, M. T. McCann, and M. Unser · 2018
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Low-dose ct via convolutional neural network
H. Chen, Y. Zhang, W. Zhang, P. Liao, K. Li, J. Zhou, and G. Wang · 2017
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Deep convolutional neural network for inverse problems in imaging
K. H. Jin, M. T. McCann, E. Froustey, and M. Unser · 2017
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A deep convolutional neural network using directional wavelets for low-dose x-ray ct reconstruction
E. Kang, J. Min, and J. C. Ye · 2017
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Nett: Solving inverse problems with deep neural networks
H. Li, J. Schwab, S. Antholzer, and M. Haltmeier · 2018
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A deep cascade of convolutional neural networks for dynamic mr image reconstruction
J. Schlemper, J. Caballero, J. V Hajnal, A. N. Price, and D. Rueckert · 2018
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