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Zhu, R. 
ORCID: 0000-0002-9944-0369, Guo, Y. and Xue, J-H. (2020).
Adjusting the imbalance ratio by the dimensionality of imbalanced data.
Pattern Recognition Letters,
doi: 10.1016/j.patrec.2020.03.004
Bai, W., Suzuki, H., Huang, J., Francis, C., Wang, S., Tarroni, G. ORCID: 0000-0002-0341-6138, Guitton, F., Aung, N., Fung, K., Petersen, S. E., Piechnik, S. K., Neubauer, S., Evangelou, E., Dehghan, A., O'Regan, D., Wilkinson, M., Guo, Y., Matthews, P. M. and Rueckert, D. (2020).
A population-based phenome-wide association study of cardiac and aortic structure and function.
Nature Medicine, 26(10),
pp. 1654-1662.
doi: 10.1038/s41591-020-1009-y
Yu, S., Dong, H., Yang, G., Slabaugh, G. G., Dragotti, P. L., Ye, X., Liu, F., Arridge, S., Keegan, J., Firmin, D. and Guo, Y. (2017). Deep De-Aliasing for Fast Compressive Sensing MRI. IEEE Transactions on Medical Imaging,
Wu, W., Zhang, H., Wang, Y., Ye, S., Guo, Y., Di, C., Yu, G., Zhu, D. and Liu, Y. (2008). High-performance organic transistor memory elements with steep flanks of hysteresis. Advanced Functional Materials, 18(17), pp. 2593-2601. doi: 10.1002/adfm.200701269
Wang, S., Tarroni, G. ORCID: 0000-0002-0341-6138, Qin, C., Mo, Y., Dai, C., Chen, C., Glocker, B., Guo, Y., Rueckert, D. and Bai, W. (2020).
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation.
Paper presented at the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, 04 - 08 October 2020, Lima, Peru.
Bai, W., Chen, C., Tarroni, G. ORCID: 0000-0002-0341-6138, Duan, J., Guitton, F., Petersen, S. E., Guo, Y., Matthews, P. M. and Rueckert, D. (2019).
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction.
In: Shen, D., Liu, T., Peters, T. M., Staib, L. H., Essert, C., Zhou, S., Yap, P-T. and Khan, A. (Eds.),
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. Lecture Notes in Computer Science, vol 11765.
(pp. 541-549). Cham: Springer.
ISBN 9783030322441