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Multi-contrast MRI (MC-MRI) captures multiple complementary imaging modalities to aid in radiological decision-making.
Sparse mri: The application of compressed sensing for rapid mr imaging
Michael Lustig, David Donoho, and John M Pauly · 2007
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Message-passing algorithms for compressed sensing
David L Donoho, Arian Maleki, and Andrea Montanari · 2009
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Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion mri
Ricardo Otazo, Daniel Kim, Leon Axel, and Daniel K Sodickson · 2010
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Fast multi-contrast mri reconstruction
Junzhou Huang, Chen Chen, and Leon Axel · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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The multimodal brain tumor image segmentation benchmark (brats)
Bjoern H Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, et al · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
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Accelerating magnetic resonance imaging via deep learning
Shanshan Wang, Zhenghang Su, Leslie Ying, Xi Peng, Shun Zhu, Feng Liang, Dagan Feng, and Dong Liang · 2016
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Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features
Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin S Kirby, John B Freymann, Keyvan Farahani, and Christos Davatzikos · 2017
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A deep cascade of convolutional neural networks for dynamic mr image reconstruction
Jo Schlemper, Jose Caballero, Joseph V Hajnal, Anthony N Price, and Daniel Rueckert · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Modl: Model-based deep learning architecture for inverse problems
Hemant K Aggarwal, Merry P Mani, and Mathews Jacob · 2018
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Deep-learning-assisted diagnosis for knee magnetic resonance imaging: development and retrospective validation of mrnet
Nicholas Bien, Pranav Rajpurkar, Robyn L Ball, Jeremy Irvin, Allison Park, Erik Jones, Michael Bereket, Bhavik N Patel, Kristen W Yeom, Katie Shpanskaya, et al · 2018
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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
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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 · 2018
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Convolutional recurrent neural networks for dynamic mr image reconstruction
Chen Qin, Jo Schlemper, Jose Caballero, Anthony N Price, Joseph V Hajnal, and Daniel Rueckert · 2018
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Ultra-fast t2-weighted mr reconstruction using complementary t1-weighted information
Lei Xiang, Yong Chen, Weitang Chang, Yiqiang Zhan, Weili Lin, Qian Wang, and Dinggang Shen · 2018
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fastmri: An open dataset and benchmarks for accelerated mri
Jure Zbontar, Florian Knoll, Anuroop Sriram, Tullie Murrell, Zhengnan Huang, Matthew J Muckley, Aaron Defazio, Ruben Stern, Patricia Johnson, Mary Bruno, et al · 2018
Tuning-free plug-and-play proximal algorithm for inverse imaging problems
Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, and Hua Huang · 2020
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Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data
Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Jutta Ellermann, Kâmil Uğurbil, and Mehmet Akçakaya · 2020
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Dudornet: Learning a dual-domain recurrent network for fast mri reconstruction with deep t1 prior
Bo Zhou and S Kevin Zhou · 2020
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Pre-trained image processing transformer
Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu, and Wen Gao · 2021
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Over-and-under complete convolutional rnn for mri reconstruction
Pengfei Guo, Jeya Maria Jose Valanarasu, Puyang Wang, Jinyuan Zhou, Shanshan Jiang, and Vishal M Patel · 2021
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Ista-net: Interpretable optimization-inspired deep network for image compressive sensing
Jian Zhang and Bernard Ghanem · 2018
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Image reconstruction by domain-transform manifold learning
Bo Zhu, Jeremiah Z Liu, Stephen F Cauley, Bruce R Rosen, and Matthew S Rosen · 2018
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A deep information sharing network for multi-contrast compressed sensing mri reconstruction
Liyan Sun, Zhiwen Fan, Xueyang Fu, Yue Huang, Xinghao Ding, and John Paisley · 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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Prior-guided image reconstruction for accelerated multi-contrast mri via generative adversarial networks
Salman UH Dar, Mahmut Yurt, Mohammad Shahdloo, Muhammed Emrullah Ildız, Berk Tınaz, and Tolga Çukur · 2020
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fastmri: A publicly available raw k-space and dicom dataset of knee images for accelerated mr image reconstruction using machine learning
Florian Knoll, Jure Zbontar, Anuroop Sriram, Matthew J Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J Geras, Joe Katsnelson, Hersh Chandarana, et al · 2020
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Active mr k-space sampling with reinforcement learning
Luis Pineda, Sumana Basu, Adriana Romero, Roberto Calandra, and Michal Drozdzal · 2020
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Self-supervised learning for mri reconstruction with a parallel network training framework
Chen Hu, Cheng Li, Haifeng Wang, Qiegen Liu, Hairong Zheng, and Shanshan Wang · 2021
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Swinir: Image restoration using swin transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
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Deep unregistered multi-contrast mri reconstruction
Xinwen Liu, Jing Wang, Jin Jin, Mingyan Li, Fangfang Tang, Stuart Crozier, and Feng Liu · 2021
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Universal undersampled mri reconstruction
Xinwen Liu, Jing Wang, Feng Liu, and S Kevin Zhou · 2021
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On the regularization of feature fusion and mapping for fast mr multi-contrast imaging via iterative networks
Xinwen Liu, Jing Wang, Hongfu Sun, Shekhar S Chandra, Stuart Crozier, and Feng Liu · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Uformer: A general u-shaped transformer for image restoration
Zhendong Wang, Xiaodong Cun, Jianmin Bao, and Jianzhuang Liu · 2021
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Unsupervised mri reconstruction via zero-shot learned adversarial transformers
Yilmaz Korkmaz, Salman UH Dar, Mahmut Yurt, Muzaffer Özbey, and Tolga Cukur · 2022
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Zero-shot self-supervised learning for MRI reconstruction
Burhaneddin Yaman, Seyed Amir Hossein Hosseini, and Mehmet Akcakaya · 2022
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Dual-domain self-supervised learning for accelerated non-cartesian mri reconstruction
Bo Zhou, Jo Schlemper, Neel Dey, Seyed Sadegh Mohseni Salehi, Kevin Sheth, Chi Liu, James S Duncan, and Michal Sofka · 2022
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