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Deep learning approaches have recently shown great promise in accelerating magnetic resonance image (MRI) acquisition.
The optimal control of partially observable markov processes
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Leslie Pack Kaelbling, Michael L Littman, and Anthony R Cassandra · 1998
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Matplotlib: A 2d graphics environment
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Sparse mri: The application of compressed sensing for rapid mr imaging
Michael Lustig, David Donoho, and John Pauly · 2007
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Applicability and efficiency of near-optimal spatial encoding for dynamically adaptive mri
Gary P Zientara, Lawrence P Panych, and Ferenc A Jolesz · 2007
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Optimization of k-space trajectories for compressed sensing by bayesian experimental design
Matthias Seeger, Hannes Nickisch, Rolf Pohmann, and Bernhard Schölkopf · 2010
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Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al · 2011
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Adaptive sampling design for compressed sensing mri
Saiprasad Ravishankar and Yoram Bresler · 2011
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Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Stefan Van der Walt, Johannes L Schönberger, Juan Nunez-Iglesias, François Boulogne, Joshua D Warner, Neil Yager, Emmanuelle Gouillart, and Tony Yu · 2014
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Energy preserved sampling for compressed sensing mri
Yudong Zhang, Bradley S Peterson, Genlin Ji, and Zhengchao Dong · 2014
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Learning-based compressive mri
Baran Gözcü, Rabeeh Karimi Mahabadi, Yen-Huan Li, Efe Ilıcak, Tolga Çukur, Jonathan Scarlett, and Volkan Cevher · 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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Richard S. Sutton and Andrew G. Barto · 2018
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fastMRI: An open dataset and benchmarks for accelerated MRI
Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J. Muckley, Mary Bruno, et al · 2018
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Multi-channel generative adversarial network for parallel magnetic resonance image reconstruction in k-space
Pengyue Zhang, Fusheng Wang, Wei Xu, and Yu Li · 2018
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Jupyter notebooks-a publishing format for reproducible computational workflows
Thomas Kluyver, Benjamin Ragan-Kelley, Fernando Pérez, Brian E Granger, Matthias Bussonnier, Jonathan Frederic, Kyle Kelley, Jessica B Hamrick, Jason Grout, Sylvain Corlay, et al · 2016
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Deep reinforcement learning with double q-learning
Hado Van Hasselt, Arthur Guez, and David Silver · 2016
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Accelerating magnetic resonance imaging via deep learning
S. Wang, Z. Su, L. Ying, X. Peng, S. Zhu, F. Liang, D. Feng, and D. Liang · 2016
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Learning a variational network for reconstruction of accelerated mri data
Kerstin Hammernik, Teresa Klatzer, Erich Kobler, Michael P. Recht, Daniel K. Sodickson, Thomas Pock, and Florian Knoll · 2017
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Variable-density single-shot fast spin-echo mri with deep learning reconstruction by using variational networks
Feiyu Chen, V. Taviani, Itzik Malkiel, Joseph Cheng, Jonathan Tamir, Jamil Shaikh, Stephanie Chang, Christopher Hardy, John Pauly, and Shreyas Vasanawala · 2018
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Image reconstruction by domain transform manifold learning
Bo Zhu, Jeremiah Zhe Liu, Bruce Rosen, and Matthew Rosen · 2018
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Self-supervised deep active accelerated mri
Kyong Hwan Jin, Michael Unser, and Kwang Moo Yi · 2019
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Recurrent inference machines for reconstructing heterogeneous mri data
Kai Lønning, Patrick Putzky, Jan-Jakob Sonke, Liesbeth Reneman, Matthan Caan, and Max Welling · 2019
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Reinforcement learning in healthcare: A survey
Chao Yu, Jiming Liu, and Shamim Nemati · 2019
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Reducing uncertainty in undersampled MRI reconstruction with active acquisition
Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, and Michal Drozdzal · 2019
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Deepcomplexmri: Exploiting deep residual network for fast parallel mr imaging with complex convolution
Shanshan Wang, Huitao Cheng, Leslie Ying, Taohui Xiao, Ziwen Ke, Hairong Zheng, and Dong Liang · 2020
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