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Image domain prior models have been shown to improve the quality of reconstructed images, especially when data are limited.
“Reduction of metal streak artifacts in x-ray computed tomography using a transmission maximum a posteriori algorithm,”
Bruno De Man, Johan Nuyts, Patrick Dupont, Guy Marchal, and Paul Suetens, · 2000
Earlier work this paper cites.
“Image inpainting,”
Marcelo Bertalmio, Guillermo Sapiro, Vincent Caselles, and Coloma Ballester, · 2000
Earlier work this paper cites.
“Statistical image reconstruction for polyenergetic X-ray computed tomography,”
Idris A Elbakri and Jeffrey A Fessler, · 2002
Earlier work this paper cites.
“Penalized-likelihood sinogram smoothing for low-dose CT,”
Patrick J La Riviere, · 2005
Earlier work this paper cites.
Deblurring images: matrices, spectra, and filtering
Per Christian Hansen, James G Nagy, and Dianne P O’leary, · 2006
Earlier work this paper cites.
“Single-pixel imaging via compressive sampling,”
Marco F Duarte, Mark A Davenport, Dharmpal Takhar, Jason N Laska, Ting Sun, Kevin F Kelly, and Richard G Baraniuk, · 2008
Earlier work this paper cites.
“Improved total variation-based CT image reconstruction applied to clinical data,”
Ludwig Ritschl, Frank Bergner, Christof Fleischmann, and Marc Kachelrieß, · 2011
Earlier work this paper cites.
“Denoising mr spectroscopic imaging data with low-rank approximations,”
Hien M Nguyen, Xi Peng, Minh N Do, and Zhi-Pei Liang, · 2012
Earlier work this paper cites.
“Low-rank modeling of local
Justin P Haldar, · 2013
Earlier work this paper cites.
“Plug-and-play priors for model based reconstruction,”
Singanallur V Venkatakrishnan, Charles A Bouman, and Brendt Wohlberg, · 2013
Earlier work this paper cites.
“Multiplexed coded illumination for fourier ptychography with an led array microscope,”
Lei Tian, Xiao Li, Kannan Ramchandran, and Laura Waller, · 2014
Earlier work this paper cites.
“Sparsity-driven synthetic aperture radar imaging: Reconstruction, autofocusing, moving targets, and compressed sensing,”
Mujdat Cetin, Ivana Stojanovic, Ozben Onhon, Kush Varshney, Sadegh Samadi, William Clem Karl, and Alan S Willsky, · 2014
Earlier work this paper cites.
“Generative adversarial nets,”
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio, · 2014
Earlier work this paper cites.
“Advances in automatic target recognition (ATR) for CT based object detection system–Final report, Dept,”
C Crawford, · 2014
Earlier work this paper cites.
“Adam: A method for stochastic optimization,”
Diederik Kingma and Jimmy Ba, · 2014
Earlier work this paper cites.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in
2014
Earlier work this paper cites.
D. Kingma and J. Ba, “Adam: A method for stochastic optimization,”
2014
Earlier work this paper cites.
“A Model-Based Image Reconstruction Algorithm With Simultaneous Beam Hardening Correction for X-Ray CT.,”
Pengchong Jin, Charles A Bouman, and Ken D Sauer, · 2015
Earlier work this paper cites.
“U-net: Convolutional networks for biomedical image segmentation,”
Olaf Ronneberger, Philipp Fischer, and Thomas Brox, · 2015
Earlier work this paper cites.
O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in
2015
Earlier work this paper cites.
“A Gaussian mixture MRF for model-based iterative reconstruction with applications to low-dose X-ray CT,”
Ruoqiao Zhang, Dong Hye Ye, Debashish Pal, Jean-Baptiste Thibault, Ken D Sauer, and Charles A Bouman, · 2016
Earlier work this paper cites.
“Compressive dynamic aperture b-mode ultrasound imaging using annihilating filter-based low-rank interpolation,”
Kyong Hwan Jin, Yo Seob Han, and Jong Chul Ye, · 2016
Earlier work this paper cites.
“Plug-and-play priors for bright field electron tomography and sparse interpolation,”
Suhas Sreehari, S Venkat Venkatakrishnan, Brendt Wohlberg, Gregery T Buzzard, Lawrence F Drummy, Jeffrey P Simmons, and Charles A Bouman, · 2016
Cited alongside, same era.
“Accurate image super-resolution using very deep convolutional networks,”
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee, · 2016
Cited alongside, same era.
“Fast and flexible X-ray tomography using the ASTRA toolbox,”
Wim van Aarle, Willem Jan Palenstijn, Jeroen Cant, Eline Janssens, Folkert Bleichrodt, Andrei Dabravolski, Jan De Beenhouwer, K Joost Batenburg, and Jan Sijbers, · 2016
Cited alongside, same era.
“Modeling and pre-treatment of photon-starved CT data for iterative reconstruction,”
Zhiqian Chang, Ruoqiao Zhang, Jean-Baptiste Thibault, Debashish Pal, Lin Fu, Ken Sauer, and Charles Bouman, · 2017
Cited alongside, same era.
“Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion,”
Rushil Anirudh, Hyojin Kim, Jayaraman J Thiagarajan, K Aditya Mohan, Kyle Champley, and Timo Bremer, · 2017
“Plug-and-play unplugged: Optimization-free reconstruction using consensus equilibrium,”
Gregery T Buzzard, Stanley H Chan, Suhas Sreehari, and Charles A Bouman, · 2018
Later among the works it cites.
“Cnn-based projected gradient descent for consistent ct image reconstruction,”
Harshit Gupta, Kyong Hwan Jin, Ha Q Nguyen, Michael T McCann, and Michael Unser, · 2018
Later among the works it cites.
“Regularization by denoising: Clarifications and new interpretations,”
Edward T Reehorst and Philip Schniter, · 2018
Later among the works it cites.
“Framing U-Net via deep convolutional framelets: Application to sparse-view CT,”
Yoseob Han and Jong Chul Ye, · 2018
Later among the works it cites.
“Deep-Neural-Network-Based Sinogram Synthesis for Sparse-View CT Image Reconstruction,”
Hoyeon Lee, Jongha Lee, Hyeongseok Kim, Byungchul Cho, and Seungryong Cho, · 2018
Later among the works it cites.
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Cited alongside, same era.
“Learning proximal operators: Using denoising networks for regularizing inverse imaging problems,”
Tim Meinhardt, Michael Moller, Caner Hazirbas, and Daniel Cremers, · 2017
Cited alongside, same era.
“Primal-dual plug-and-play image restoration,”
Shunsuke Ono, · 2017
Cited alongside, same era.
“A plug-and-play priors approach for solving nonlinear imaging inverse problems,”
Ulugbek S Kamilov, Hassan Mansour, and Brendt Wohlberg, · 2017
Cited alongside, same era.
“The little engine that could: Regularization by denoising (RED),”
Yaniv Romano, Michael Elad, and Peyman Milanfar, · 2017
Cited alongside, same era.
“Image-to-Image Translation with Conditional Adversarial Networks,”
P. Isola, J. Y. Zhu, T. Zhou, and A. A. Efros, · 2017
Cited alongside, same era.
“Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising,”
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang, · 2017
Cited alongside, same era.
“Deep convolutional neural network for inverse problems in imaging,”
Kyong Hwan Jin, Michael T McCann, Emmanuel Froustey, and Michael Unser, · 2017
Cited alongside, same era.
Kaichao Liang, Hongkai Yang, and Yuxiang Xing, · 2018
Later among the works it cites.
“fastmri: An open dataset and benchmarks for accelerated mri,”
Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J Geras, Joe Katsnelson, Hersh Chandarana, et al., · 2018
Later among the works it cites.
“Deep residual learning for accelerated mri using magnitude and phase networks,”
Dongwook Lee, Jaejun Yoo, Sungho Tak, and Jong Chul Ye, · 2018
Later among the works it cites.
“Kiki-net: cross-domain convolutional neural networks for reconstructing undersampled magnetic resonance images,”
Taejoon Eo, Yohan Jun, Taeseong Kim, Jinseong Jang, Ho-Joon Lee, and Dosik Hwang, · 2018
Later among the works it cites.
“Iterative pet image reconstruction using convolutional neural network representation,”
Kuang Gong, Jiahui Guan, Kyungsang Kim, Xuezhu Zhang, Jaewon Yang, Youngho Seo, Georges El Fakhri, Jinyi Qi, and Quanzheng Li, · 2018
Later among the works it cites.
“Data consistent artifact reduction for limited angle tomography with deep learning prior,”
Yixing Huang, Alexander Preuhs, Günter Lauritsch, Michael Manhart, Xiaolin Huang, and Andreas Maier, · 2019
Later among the works it cites.
“Learning the invisible: A hybrid deep learning-shearlet framework for limited angle computed tomography,”
Tatiana A Bubba, Gitta Kutyniok, Matti Lassas, Maximilian Maerz, Wojciech Samek, Samuli Siltanen, and Vignesh Srinivasan, · 2019
Later among the works it cites.
“k-space deep learning for accelerated mri,”
Yoseob Han, Leonard Sunwoo, and Jong Chul Ye, · 2019
Later among the works it cites.
“Structured low-rank algorithms: Theory, mr applications, and links to machine learning,”
Mathews Jacob, Merry P Mani, and Jong Chul Ye, · 2019
Later among the works it cites.
“High frame-rate ultrasound imaging using deep learning beamforming,”
Muhammad Usman Ghani, F Can Meral, Francois Vignon, and Jean-luc Robert, · 2019
Later among the works it cites.
“Integrating data and image domain deep learning for limited angle tomography using consensus equilibrium,”
Muhammad Usman Ghani and W. Clem Karl, · 2019
Later among the works it cites.
“Sinogram interpolation for sparse-view micro-ct with deep learning neural network,”
Xu Dong, Swapnil Vekhande, and Guohua Cao, · 2019
Later among the works it cites.
M. U. Ghani and W. C. Karl, “Integrating data and image domain deep learning for limited angle tomography using consensus equilibrium,” in
2019
Later among the works it cites.
Y. Han, L. Sunwoo, and J. C. Ye, “k-space deep learning for accelerated mri,”
2019
Later among the works it cites.
“Reconstruction for diverging-wave imaging using deep convolutional neural networks,”
Jingfeng Lu, Fabien Millioz, Damien Garcia, Sébastien Salles, Wanyu Liu, and Denis Friboulet, · 2020
Closest in time.
“Plug-and-play methods for magnetic resonance imaging: Using denoisers for image recovery,”
Rizwan Ahmad, Charles A Bouman, Gregery T Buzzard, Stanley Chan, Sizhuo Liu, Edward T Reehorst, and Philip Schniter, · 2020
Closest in time.
M. U. Ghani and W. C. Karl, “Data and image prior integration for image reconstruction using consensus equilibrium,”
2020
Closest in time.