3 citations · 8 across the 19 of their papers we have counts for
4 papers · 1 filter
Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learning
Yiwen Ye, Yutong Xie, Jianpeng Zhang +3
Self-supervised learning is an efficient pre-training method for medical image analysis. However, current research is mostly confined to specific-modality data pre-training, consum…
Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation
Ziyang Chen, Yongsheng Pan, Yiwen Ye +2
Distribution shift widely exists in medical images acquired from different medical centres and poses a significant obstacle to deploying the pre-trained semantic segmentation model…
Treasure in Distribution: A Domain Randomization based Multi-Source Domain Generalization for 2D Medical Image Segmentation
Ziyang Chen, Yongsheng Pan, Yiwen Ye +2
Although recent years have witnessed the great success of convolutional neural networks (CNNs) in medical image segmentation, the domain shift issue caused by the highly variable i…
UniSeg: A Prompt-driven Universal Segmentation Model as well as A Strong Representation Learner
Yiwen Ye, Yutong Xie, Jianpeng Zhang +2
The universal model emerges as a promising trend for medical image segmentation, paving up the way to build medical imaging large model (MILM). One popular strategy to build univer…