Items where Author is "Bai, W."
Article
Chen, C., Qin, C., Ouyang, C. (2022). Enhancing MR image segmentation with realistic adversarial data augmentation. Medical Image Analysis, 82, article number 102597. doi: 10.1016/j.media.2022.102597
Sriram, V., Agarwal, S., Yan, S. ORCID: 0000-0001-8968-6616 (2021).
A Comparative Study on the Nonlinear Interaction Between a Focusing Wave and Cylinder Using State-of-the-art Solvers: Part A.
International Journal of Offshore and Polar Engineering, 31(1),
pp. 1-10.
doi: 10.17736/ijope.2021.jc820
Bai, W., Suzuki, H., Huang, J. (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
Biffi, C., Cerrolaza, J. J., Tarroni, G. ORCID: 0000-0002-0341-6138 (2020).
Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models.
IEEE Transactions on Medical Imaging, 39(6),
pp. 2088-2099.
doi: 10.1109/tmi.2020.2964499
Chen, C., Qin, C., Qiu, H. (2020). Deep Learning for Cardiac Image Segmentation: A Review. Frontiers in Cardiovascular Medicine, 7, article number 25. doi: 10.3389/fcvm.2020.00025
Ransley, E., Yan, S. ORCID: 0000-0001-8968-6616, Brown, S. (2020).
A Blind Comparative Study of Focused Wave Interactions with Floating Structures (CCP-WSI Blind Test Series 3).
International Journal of Offshore and Polar Engineering, 30(1),
pp. 1-10.
doi: 10.17736/ijope.2020.jc774
Tarroni, G. ORCID: 0000-0002-0341-6138, Bai, W., Oktay, O. (2020).
Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank.
Scientific Reports, 10(1),
article number 2408.
doi: 10.1038/s41598-020-58212-2
Tarroni, G. ORCID: 0000-0002-0341-6138, Oktay, O., Bai, W. (2019).
Learning-based quality control for cardiac MR images.
IEEE Transactions on Medical Imaging, 38(5),
pp. 1127-1138.
doi: 10.1109/tmi.2018.2878509
Bai, W., Sinclair, M., Tarroni, G. ORCID: 0000-0002-0341-6138 (2018).
Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.
Journal of Cardiovascular Magnetic Resonanc, 20(1),
article number 65.
doi: 10.1186/s12968-018-0471-x
Conference or Workshop Item
Wang, S., Tarroni, G. ORCID: 0000-0002-0341-6138, Qin, C. (2020).
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020.
23rd International Conference on Medical Image Computing and Computer Assisted Intervention, 04 - 08 October 2020, Lima, Peru.
doi: 10.1007/978-3-030-59719-1_9
Chen, C., Qin, C., Qiu, H. (2020). Realistic Adversarial Data Augmentation for MR Image Segmentation. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. 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 (2020).
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation.
In: Pop, M., Sermesant, M., Camara, O. (Eds.),
Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges. STACOM 2019.
STACOM 2019, 13 Oct 2019, Shenzen, China.
doi: 10.1007/978-3-030-39074-7_22
Bai, W., Chen, C., Tarroni, G. ORCID: 0000-0002-0341-6138 (2019).
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction.
In: Shen, D., Liu, T., Peters, T. M. (Eds.),
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. Lecture Notes in Computer Science, vol 11765.
Tarroni, G. ORCID: 0000-0002-0341-6138, Oktay, O., Sinclair, M. (2018).
A Comprehensive Approach for Learning-Based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018.
doi: 10.1007/978-3-030-00928-1_31
Biffi, C., Oktay, O., Tarroni, G. ORCID: 0000-0002-0341-6138 (2018).
Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling.
In:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018. MICCAI 2018.
doi: 10.1007/978-3-030-00934-2_52
Bai, W., Suzuki, H., Qin, C. (2018). Recurrent Neural Networks for Aortic Image Sequence Segmentation with Sparse Annotations. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018. doi: 10.1007/978-3-030-00937-3_67
Working Paper
Chen, C., Qin, C., Qiu, H. (2019). Deep learning for cardiac image segmentation: A review. City, university of London.