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Magnetic Resonance Imaging (MRI) has become an important technique in the clinic for the visualization, detection, and diagnosis of various diseases.
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2008
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2016
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2017
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Eo, Taejoon and Jun, Yohan and Kim, Taeseong and Jang, Jinseong and Lee, Ho-Joon and Hwang, Dosik, “KIKI-net: cross-domain convolutional neural networks for reconstructing undersampled magnetic resonance images,” Magnetic resonance in medicine , vol. 80, no. 5, pp. 2188–2201, 2018
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Zhang, Jian and Ghanem, Bernard, “ISTA-Net: Interpretable optimization-inspired deep network for image compressive sensing,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2018, pp. 1828–1837
2018
Cited alongside, same era.
Aggarwal, Hemant K and Mani, Merry P and Jacob, Mathews, “MoDL: Model-based deep learning architecture for inverse problems,” IEEE transactions on medical imaging , vol. 38, no. 2, pp. 394–405, 2018
2018
Cited alongside, same era.
Hammernik, Kerstin and Klatzer, Teresa and Kobler, Erich and Recht, Michael P and Sodickson, Daniel K and Pock, Thomas and Knoll, Florian, “Learning a variational network for reconstruction of accelerated MRI data,” Magnetic resonance in medicine , vol. 79, no. 6, pp. 3055–3071, 2018
2018
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Akçakaya, Mehmet and Moeller, Steen and Weingärtner, Sebastian and Uğurbil, Kâmil, “Scan-specific robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction: Database-free deep learning for fast imaging,” Magnetic resonance in medicine , vol. 81, no. 1, pp. 439–453, 2019
2019
Later among the works it cites.
Yaman, Burhaneddin and Hosseini, Seyed Amir Hossein and Moeller, Steen and Ellermann, Jutta and Uğurbil, Kâmil and Akçakaya, Mehmet, “Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data,” Magnetic resonance in medicine , vol. 84, no. 6, pp. 3172–3191, 2020
2020
Later among the works it cites.
Wang, Shanshan and Xiao, Taohui and Liu, Qiegen and Zheng, Hairong, “Deep learning for fast MR imaging: a review for learning reconstruction from incomplete k-space data,” Biomedical Signal Processing and Control , vol. 68, p. 102579, 2021
2021
Later among the works it cites.
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2018
Cited alongside, same era.
Ye, Jong Chul, “Compressed sensing MRI: a review from signal processing perspective,” BMC Biomedical Engineering , vol. 1, no. 1, pp. 1–17, 2019
2019
Cited alongside, same era.
Wang, Shanshan and Cao, Guohua and Wang, Yan and Liao, Shu and Wang, Qian and Shi, Jun and Li, Cheng and Shen, Dinggang, “Review and Prospect: Artificial Intelligence in Advanced Medical Imaging,” Frontiers in Radiology , vol. 1, p. 781868, 2021
2021
Later among the works it cites.
Li, Cheng and Li, Wen and Liu, Chenyang and Zheng, Hairong and Cai, Jing and Wang, Shanshan, “Artificial intelligence in multiparametric magnetic resonance imaging: A review,” Medical Physics , 2022
2022
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