Papers by Lin Xian and Wu Nannan Accepted by MICCAI

Recently, the paper ‘ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation’ by our lab’s student Lin Xian, and the paper ‘FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification’ by student Wu Nannan, have been accepted by the international conference International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). MICCAI is one of the most important international conferences in the field of medical image processing, a CCF-B conference, with high academic influence.