3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CV2026
Rethinking the Efficiency and Effectiveness of Reinforcement Learning for Radiology Report Generation
Zilin Lu, Ruifeng Yuan, Weiwei Cao +6
Radiologists highly desire fully automated AI for radiology report generation (R2G), yet existing approaches fall short in clinical utility. Reinforcement learning (RL) holds poten…
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★ 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…