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The novel coronavirus disease 2019 (COVID-19) has been spreading rapidly around the world and caused significant impact on the public health and economy.
M. D. Zeiler, D. Krishnan, G. W. Taylor, and R. Fergus, “Deconvolutional networks,” in 2010 IEEE Computer Society Conference on computer vision and pattern recognition . IEEE, 2010, pp. 2528–2535
2010
Earlier work this paper cites.
I. Sutskever, O. Vinyals, and Q. V. Le, “Sequence to sequence learning with neural networks,” in Advances in neural information processing systems , 2014, pp. 3104–3112
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in International Conference on Medical image computing and computer-assisted intervention . Springer, 2015, pp. 234–241
2015
Earlier work this paper cites.
J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 3431–3440
2015
Earlier work this paper cites.
K. He and J. Sun, “Convolutional neural networks at constrained time cost,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 5353–5360
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 770–778
2016
Earlier work this paper cites.
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba, “Learning deep features for discriminative localization,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 2921–2929
2016
Earlier work this paper cites.
D. Shen, G. Wu, and H.-I. Suk, “Deep learning in medical image analysis,” Annual review of biomedical engineering , vol. 19, pp. 221–248, 2017
2017
Earlier work this paper cites.
C. F. Baumgartner, L. M. Koch, M. Pollefeys, and E. Konukoglu, “An exploration of 2d and 3d deep learning techniques for cardiac mr image segmentation,” in International Workshop on Statistical Atlases and Computational Models of the Heart . Springer, 2017, pp. 111–119
2017
Earlier work this paper cites.
S. Xie, R. Girshick, P. Dollár, Z. Tu, and K. He, “Aggregated residual transformations for deep neural networks,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 1492–1500
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” in Advances in neural information processing systems , 2017, pp. 5998–6008
2017
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
K. Chen, L. Yao, X. Wang, D. Zhang, T. Gu, Z. Yu, and Z. Yang, “Interpretable parallel recurrent neural networks with convolutional attentions for multi-modality activity modeling,” in 2018 International Joint Conference on Neural Networks (IJCNN) . IEEE, 2018, pp. 1–8
C. Long, H. Xu, Q. Shen, X. Zhang, B. Fan, C. Wang, B. Zeng, Z. Li, X. Li, and H. Li, “Diagnosis of the coronavirus disease (covid-19): rrt-pcr or ct?” European Journal of Radiology , p. 108961, 2020
2020
Closest in time.
T. Ai, Z. Yang, H. Hou, C. Zhan, C. Chen, W. Lv, Q. Tao, Z. Sun, and L. Xia, “Correlation of chest ct and rt-pcr testing in coronavirus disease 2019 (covid-19) in china: a report of 1014 cases,” Radiology , p. 200642, 2020
2020
Closest in time.
Y. Li and L. Xia, “Coronavirus disease 2019 (covid-19): Role of chest ct in diagnosis and management,” American Journal of Roentgenology , pp. 1–7, 2020
2020
Closest in time.
S. Salehi, A. Abedi, S. Balakrishnan, and A. Gholamrezanezhad, “Coronavirus disease 2019 (COVID-19): a systematic review of imaging findings in 919 patients,” American Journal of Roentgenology , pp. 1–7, 2020
2020
Closest in time.
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2018
Cited alongside, same era.
2018
Cited alongside, same era.
C. Ye, W. Wang, S. Zhang, and K. Wang, “Multi-depth fusion network for whole-heart ct image segmentation,” IEEE Access , vol. 7, pp. 23 421–23 429, 2019
2019
Cited alongside, same era.
Z. Liu, Y.-Q. Song, V. S. Sheng, L. Wang, R. Jiang, X. Zhang, and D. Yuan, “Liver ct sequence segmentation based with improved u-net and graph cut,” Expert Systems with Applications , vol. 126, pp. 54–63, 2019
2019
Cited alongside, same era.
X. Dong, Y. Lei, T. Wang, M. Thomas, L. Tang, W. J. Curran, T. Liu, and X. Yang, “Automatic multiorgan segmentation in thorax ct images using u-net-gan,” Medical physics , vol. 46, no. 5, pp. 2157–2168, 2019
2019
Cited alongside, same era.
2019
Cited alongside, same era.
N. Zhu, D. Zhang, W. Wang, X. Li, B. Yang, J. Song, X. Zhao, B. Huang, W. Shi, R. Lu et al. , “A novel coronavirus from patients with pneumonia in china, 2019,” New England Journal of Medicine , 2020
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2020
Cited alongside, same era.
C. Huang, Y. Wang, X. Li, L. Ren, J. Zhao, Y. Hu, L. Zhang, G. Fan, J. Xu, X. Gu et al. , “Clinical features of patients infected with 2019 novel coronavirus in wuhan, china,” The Lancet , vol. 395, no. 10223, pp. 497–506, 2020
2020
Closest in time.
L.-s. Wang, Y.-r. Wang, D.-w. Ye, and Q.-q. Liu, “A review of the 2019 novel coronavirus (covid-19) based on current evidence,” International Journal of Antimicrobial Agents , p. 105948, 2020
2020
Closest in time.
2020
Closest in time.
2020
Closest in time.
N. Ibtehaz and M. S. Rahman, “Multiresunet: Rethinking the u-net architecture for multimodal biomedical image segmentation,” Neural Networks , vol. 121, pp. 74–87, 2020
2020
Closest in time.
N. Kitaev, L. Kaiser, and A. Levskaya, “Reformer: The efficient transformer,” in International Conference on Learning Representations , 2020. [Online]. Available: https://openreview.net/forum?id=rkgNKkHtvB
2020
Closest in time.
A. Bernheim, X. Mei, M. Huang, Y. Yang, Z. A. Fayad, N. Zhang, K. Diao, B. Lin, X. Zhu, K. Li et al. , “Chest ct findings in coronavirus disease-19 (covid-19): relationship to duration of infection,” Radiology , p. 200463, 2020
2020
Closest in time.
F. Song, N. Shi, F. Shan, Z. Zhang, J. Shen, H. Lu, Y. Ling, Y. Jiang, and Y. Shi, “Emerging 2019 novel coronavirus (2019-ncov) pneumonia,” Radiology , p. 200274, 2020
2020
Closest in time.