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Plug-and-play (PnP) methods that employ application-specific denoisers have been proposed to solve inverse problems, including MRI reconstruction.
“BM3D frames and variational image deblurring,”
Aram Danielyan et al., · 2011
Earlier work this paper cites.
“Plug-and-play priors for model based reconstruction,”
Venkatakrishnan et al., · 2013
Earlier work this paper cites.
“ESPIRiT—An eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA,”
Martin Uecker et al., · 2014
Earlier work this paper cites.
“DAGAN: Deep de-aliasing generative adversarial networks for fast compressed sensing MRI reconstruction,”
Guang Yang et al., · 2017
Earlier work this paper cites.
“Primal-dual plug-and-play image restoration,”
Shunsuke Ono, · 2017
Earlier work this paper cites.
“Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising,”
Kai Zhang et al., · 2017
Earlier work this paper cites.
“Learning a variational network for reconstruction of accelerated MRI data,”
Kerstin Hammernik et al., · 2018
Cited alongside, same era.
“Noise2Noise: Learning image restoration without clean data,”
Jaakko Lehtinen et al., · 2018
Cited alongside, same era.
“Deep image prior,”
Dmitry Ulyanov et al., · 2018
Cited alongside, same era.
“Unsupervised deep basis pursuit: Learning reconstruction without ground-truth data,”
Jonathan Tamir et al., · 2019
Cited alongside, same era.
“Time-dependent deep image prior for dynamic mri,”
Kyong Jin et al., · 2019
Cited alongside, same era.
“Noise2Void-learning denoising from single noisy images,”
Alexander Krull et al., · 2019
Cited alongside, same era.
“Noise2Self: Blind denoising by self-supervision,”
Joshua Batson et al., · 2019
Later among the works it cites.
“Free-breathing cardiovascular MRI using a plug-and-play method with learned denoiser,”
Sizhuo Liu et al., · 2020
Later among the works it cites.
“Unsupervised MRI reconstruction with generative adversarial networks,”
Elizabeth Cole et al., · 2020
Later among the works it cites.
“Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data,”
Burhaneddin Yaman et al., · 2020
Later among the works it cites.
“Plug-and-play methods for magnetic resonance imaging: Using denoisers for image recovery,”
Rizwan Ahmad et al., · 2020
Later among the works it cites.
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Allard Hendriksen et al., · 2020
Later among the works it cites.