4 papers have been accepted by the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020, which will be remotely held at Lima, Peru. With an acceptance rate of ~30%, MICCAI is the top conference in the field of medical image computing. In these papers, we investigated machine learning ideas on generative modelling, latent space exploration, adversarial data augmentation etc and their applications to medical image segmentation, quality control and motion estimation problems.

  1. Chengliang Dai, Shuo Wang, Yuanhan Mo, Rui Zhou, Elsa Angelini, Yike Guo and Wenjia Bai. Suggestive annotation of brain tumour images with gradient-guided sampling. MICCAI 2020.

  2. Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert and Wenjia Bai. Deep generative model-based quality control for cardiac MRI segmentation. MICCAI 2020.

  3. Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang, Shuo Wang, Liang Chen, Giacomo Tarroni, Wenjia Bai and Daniel Rueckert. Realistic adversarial data augmentation for MR image segmentation. MICCAI 2020.

  4. Chen Qin, Shuo Wang, Chen Chen, Huaqi Qiu, Wenjia Bai and Daniel Rueckert. Biomechanics-informed neural networks for myocardial motion tracking in MRI. MICCAI 2020.