Summary
I am a Senior Lecturer (Associate Professor) jointly at Department of Computing and Department of Brain Sciences, Imperial College London.
Please visit my personal website for more information.
Selected Publications
Journal Articles
Chen C, Qin C, Ouyang C, et al., 2022, Enhancing MR image segmentation with realistic adversarial data augmentation, Medical Image Analysis, Vol:82, ISSN:1361-8415, Pages:1-15
Francis C, Futschik M, Huang J, et al., 2022, Genome-wide associations of aortic distensibility suggest causality for aortic aneurysms and brain white matter hyperintensities, Nature Communications, Vol:13, ISSN:2041-1723
Thanaj M, Mielke J, McGurk K, et al., 2022, Genetic and environmental determinants of diastolic heart function, Nature Cardiovascular Research, Vol:1, ISSN:2731-0590, Pages:361-371
Dai C, Wang S, Mo Y, et al., 2022, Suggestive annotation of brain MR images with gradient-guided sampling, Medical Image Analysis, Vol:77, ISSN:1361-8415, Pages:1-12
Bai W, Suzuki H, Huang J, et al., 2020, A population-based phenome-wide association study of cardiac and aortic structure and function, Nature Medicine, Vol:26, ISSN:1078-8956, Pages:1654-1662
Meyer H, Dawes T, Serrani M, et al., 2020, Genetic and functional insights into the fractal structure of the heart, Nature, Vol:584, ISSN:0028-0836, Pages:589-594
Chen C, Qin C, Qiu H, et al., 2020, Deep learning for cardiac image segmentation: A review, Frontiers in Cardiovascular Medicine, Vol:7, ISSN:2297-055X, Pages:1-33
Tarroni G, Oktay O, Bai W, et al., 2019, Learning-based quality control for cardiac MR images, IEEE Transactions on Medical Imaging, Vol:38, ISSN:0278-0062, Pages:1127-1138
Bai W, Sinclair M, Tarroni G, et al., 2018, Automated cardiovascular magnetic resonance image analysis with fully convolutional networks, Journal of Cardiovascular Magnetic Resonance, Vol:20, ISSN:1097-6647, Pages:1-12
Bai W, Shi W, de Marvao A, et al., 2015, A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion, Medical Image Analysis, Vol:26, ISSN:1361-8423, Pages:133-145
Bai W, Shi W, Ledig C, et al., 2015, Multi-atlas segmentation with augmented features for cardiac MR images, Medical Image Analysis, Vol:19, ISSN:1361-8415, Pages:98-109
Bai W, Shi W, O'Regan DP, et al., 2013, A probabilistic patch-based label fusion model for multi-atlas segmentation with registration refinement: application to cardiac MR images, IEEE Transactions on Medical Imaging, Vol:32, ISSN:0278-0062, Pages:1302-1315
Conference
Basaran BD, Qiao M, Matthews P, et al., Subject-specific lesion generation and pseudo-healthy synthesis for multiple sclerosis brain images, SASHIMI: Simulation and Synthesis in Medical Imaging, Springer, ISSN:0302-9743
Chen C, Li Z, Ouyang C, et al., MaxStyle: adversarial style composition for robust medical image segmentation, Medical Image Computing and Computer Assisted Interventions (MICCAI) 2022
Chen C, Hammernik K, Ouyang C, et al., 2021, Cooperative training and latent space data augmentation for robust medical image segmentation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
Wang S, Qin C, Savioli N, et al., 2021, Joint motion correction and super resolution for cardiac segmentationvia latent optimisation, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Springer, Pages:14-24
Wang S, Tarroni G, Qin C, et al., 2020, Deep generative model-based quality control for cardiac MRI segmentation, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Springer Verlag, Pages:88-97, ISSN:0302-9743
Chen C, Qin C, Qiu H, et al., 2020, Realistic adversarial data augmentation for MR image segmentation, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
Bai W, Chen C, Tarroni G, et al., 2019, Self-supervised learning for cardiac MR image segmentation by anatomicalposition prediction, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
Bai W, Suzuki H, Qin C, et al., 2018, Recurrent neural networks for aortic image sequence segmentation with sparse annotations, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), ISSN:0302-9743
Qin C, Bai W, Schlemper J, et al., 2018, Joint learning of motion estimation and segmentation for cardiac MR image sequences, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Springer Verlag, Pages:472-480
Bai W, Oktay O, Sinclair M, et al., 2017, Semi-supervised learning for network-based cardiac MR image segmentation, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Springer Verlag, Pages:253-260, ISSN:0302-9743
Oktay O, Bai W, Lee M, et al., 2016, Multi-input cardiac image super-resolution using convolutional neural networks, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Pages:246-254, ISSN:0302-9743