4 papers
Shape-intensity knowledge distillation for robust medical image segmentation
Wenhui Dong, Bo Du, Yongchao Xu
Many medical image segmentation methods have achieved impressive results. Yet, most existing methods do not take into account the shape-intensity prior information. This may lead t…
Prompting Segment Anything Model with Domain-Adaptive Prototype for Generalizable Medical Image Segmentation
Zhikai Wei, Wenhui Dong, Peilin Zhou +3
Deep learning based methods often suffer from performance degradation caused by domain shift. In recent years, many sophisticated network structures have been designed to tackle th…
MoreStyle: Relax Low-frequency Constraint of Fourier-based Image Reconstruction in Generalizable Medical Image Segmentation
Haoyu Zhao, Wenhui Dong, Rui Yu +3
The task of single-source domain generalization (SDG) in medical image segmentation is crucial due to frequent domain shifts in clinical image datasets. To address the challenge of…
Scale-aware Test-time Click Adaptation for Pulmonary Nodule and Mass Segmentation
Zhihao Li, Jiancheng Yang, Yongchao Xu +3
Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based…