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Low-dose computed tomography (LDCT) is an important topic in the field of radiology over the past decades.
A family of embedded runge-kutta formulae
John R Dormand and Peter J Prince · 1980
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Bayesian statistical reconstruction for low-dose x-ray computed tomography using an adaptive-weighting nonlocal prior
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Multi-energy ct based on a prior rank, intensity and sparsity model (prism)
Hao Gao, Hengyong Yu, Stanley Osher, and Ge Wang · 2011
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Low-dose x-ray ct reconstruction via dictionary learning
Qiong Xu, Hengyong Yu, Xuanqin Mou, Lei Zhang, Jiang Hsieh, and Ge Wang · 2012
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Image denoising of low-radiation dose coronary ct angiography by an adaptive block-matching 3d algorithm
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Cine cone beam ct reconstruction using low-rank matrix factorization: algorithm and a proof-of-principle study
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Adaptive nonlocal means filtering based on local noise level for ct denoising
Zhoubo Li, Lifeng Yu, Joshua D Trzasko, David S Lake, Daniel J Blezek, Joel G Fletcher, Cynthia H McCollough, and Armando Manduca · 2014
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Sparse-view x-ray ct reconstruction via total generalized variation regularization
Shanzhou Niu, Yang Gao, Zhaoying Bian, Jing Huang, Wufan Chen, Gaohang Yu, Zhengrong Liang, and Jianhua Ma · 2014
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Few-view image reconstruction with fractional-order total variation
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Deep learning
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A perspective on deep imaging
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Yi Zhang, Yan Wang, Weihua Zhang, Feng Lin, Yifei Pu, and Jiliu Zhou · 2016
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Low dose ct image reconstruction with learned sparsifying transform
Xuehang Zheng, Zening Lu, Saiprasad Ravishankar, Yong Long, and Jeffrey A Fessler · 2016
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Low-dose ct with a residual encoder-decoder convolutional neural network
Hu Chen, Yi Zhang, Mannudeep K Kalra, Feng Lin, Yang Chen, Peixi Liao, Jiliu Zhou, and Ge Wang · 2017
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Low-dose ct via convolutional neural network
Hu Chen, Yi Zhang, Weihua Zhang, Peixi Liao, Ke Li, Jiliu Zhou, and Ge Wang · 2017
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Il Yong Chun, Zhengyu Huang, Hongki Lim, and Jeff Fessler · 2020
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Generative adversarial networks
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Ilvr: Conditioning method for denoising diffusion probabilistic models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, and Sungroh Yoon · 2021
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Deep convolutional neural network for inverse problems in imaging
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A deep convolutional neural network using directional wavelets for low-dose x-ray ct reconstruction
Eunhee Kang, Junhong Min, and Jong Chul Ye · 2017
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Generative adversarial networks for noise reduction in low-dose ct
Jelmer M Wolterink, Tim Leiner, Max A Viergever, and Ivana Išgum · 2017
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Iterative low-dose ct reconstruction with priors trained by artificial neural network
Dufan Wu, Kyungsang Kim, Georges El Fakhri, and Quanzheng Li · 2017
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Learned primal-dual reconstruction
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Learn: Learned experts’ assessment-based reconstruction network for sparse-data ct
Hu Chen, Yi Zhang, Yunjin Chen, Junfeng Zhang, Weihua Zhang, Huaiqiang Sun, Yang Lv, Peixi Liao, Jiliu Zhou, and Ge Wang · 2018
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Diffusion models beat gans on image synthesis
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