858 citations · 941 across the 6 of their papers we have counts for
7 papers
Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning
Fuying Wang, Yuyin Zhou, Shujun Wang +2
Learning medical visual representations directly from paired radiology reports has become an emerging topic in representation learning. However, existing medical image-text joint l…
Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac Segmentation
Kang Li, Shujun Wang, Lequan Yu +1
Annotation scarcity is a long-standing problem in medical image analysis area. To efficiently leverage limited annotations, abundant unlabeled data are additionally exploited in se…
DoFE: Domain-oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen Datasets
Shujun Wang, Lequan Yu, Kang Li +3
Deep convolutional neural networks have significantly boosted the performance of fundus image segmentation when test datasets have the same distribution as the training datasets. H…
Towards Cross-modality Medical Image Segmentation with Online Mutual Knowledge Distillation
Kang Li, Lequan Yu, Shujun Wang +1
The success of deep convolutional neural networks is partially attributed to the massive amount of annotated training data. However, in practice, medical data annotations are usual…
Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization
Shujun Wang, Lequan Yu, Caizi Li +2
The generalization capability of neural networks across domains is crucial for real-world applications. We argue that a generalized object recognition system should well understand…
Dual-Teacher: Integrating Intra-domain and Inter-domain Teachers for Annotation-efficient Cardiac Segmentation
Kang Li, Shujun Wang, Lequan Yu +1
Medical image annotations are prohibitively time-consuming and expensive to obtain. To alleviate annotation scarcity, many approaches have been developed to efficiently utilize ext…