19 citations · 23 across the 6 of their papers we have counts for
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cs.CV2023★ 3 cited
Segment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentation
Qingjie Zeng, Yutong Xie, Zilin Lu +3
Annotation scarcity has become a major obstacle for training powerful deep-learning models for medical image segmentation, restricting their deployment in clinical scenarios. To ad…
cs.CV2023
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…
cs.CV2023★ 1 cited
Discrepancy Matters: Learning from Inconsistent Decoder Features for Consistent Semi-supervised Medical Image Segmentation
Qingjie Zeng, Yutong Xie, Zilin Lu +2
Semi-supervised learning (SSL) has been proven beneficial for mitigating the issue of limited labeled data especially on the task of volumetric medical image segmentation. Unlike p…