4 papers
Enhancing Reinforcement Learning for Radiology Report Generation with Evidence-aware Rewards and Self-correcting Preference Learning
Qin Zhou, Guoyan Liang, Qianyi Yang +4
Recent reinforcement learning (RL) approaches have advanced radiology report generation (RRG), yet two core limitations persist: (1) report-level rewards offer limited evidence-gro…
Advancing Medical Image Segmentation via Self-supervised Instance-adaptive Prototype Learning
Guoyan Liang, Qin Zhou, Jingyuan Chen +2
Medical Image Segmentation (MIS) plays a crucial role in medical therapy planning and robot navigation. Prototype learning methods in MIS focus on generating segmentation masks thr…
Semantic-guided Masked Mutual Learning for Multi-modal Brain Tumor Segmentation with Arbitrary Missing Modalities
Guoyan Liang, Qin Zhou, Jingyuan Chen +6
Malignant brain tumors have become an aggressive and dangerous disease that leads to death worldwide.Multi-modal MRI data is crucial for accurate brain tumor segmentation, but miss…
Learnable Retrieval Enhanced Visual-Text Alignment and Fusion for Radiology Report Generation
Qin Zhou, Guoyan Liang, Xindi Li +4
Automated radiology report generation is essential for improving diagnostic efficiency and reducing the workload of medical professionals. However, existing methods face significan…