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Chen, C., Qin, C., Ouyang, C. , Li, Z., Wang, S., Qiu, H., Chen, L., Tarroni, G. 
ORCID: 0000-0002-0341-6138, Bai, W. & Rueckert, D. (2022).
Enhancing MR image segmentation with realistic adversarial data augmentation.
Medical Image Analysis, 82,
102597.
doi: 10.1016/j.media.2022.102597
Chen, C., Qin, C., Qiu, H. , Ouyang, C., Wang, S., Chen, L., Tarroni, G. ORCID: 0000-0002-0341-6138, Bai, W. & Rueckert, D. (2020).
Realistic Adversarial Data Augmentation for MR Image Segmentation.
Paper presented at the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, 04 - 08 October 2020, Lima, Peru.
doi: 10.1007/978-3-030-59710-8_65
Chen, C., Ouyang, C., Tarroni, G. ORCID: 0000-0002-0341-6138 , Schlemper, J., Qiu, H., Bai, W. & Rueckert, D. (2020).
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation.
In: Pop, M., Sermesant, M., Camara, O. , Zhuang, X., Li, S., Young, A., Mansi, T. & Suinesiaputra, A. (Eds.),
Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges. STACOM 2019.
(pp. 209-219). Cham, Switzerland: Springer.
ISBN 978-3-030-39073-0
doi: 10.1007/978-3-030-39074-7_22