1 citations · 1 across the 6 of their papers we have counts for
5 papers · 1 filter
Separating Capability from Confidence: Grounded Dual-State Calibration for GRPO-Trained Medical Vision-Language Models
Yangyang Xie, Ke Hao, Jiaqi Liu +2
Medical vision-language models (VLMs) require confidence that reflects both answer correctness and patient-specific visual evidence. Recent GRPO-based methods optimize verbalized c…
Intracranial Aneurysm Classification and Segmentation via Tri-Axial ROI and Multi-Task Learning
Pengcheng Shi, Kaiyuan Yang, Houjing Huang +7
Intracranial aneurysms are often asymptomatic until rupture, which carries high mortality. Rupture risk assessment and treatment planning depend on both aneurysm morphology and ana…
U-VLM: Hierarchical Vision Language Modeling for Report Generation
Pengcheng Shi, Minghui Zhang, Kehan Song +3
Automated radiology report generation is key for reducing radiologist workload and improving diagnostic consistency, yet generating accurate reports for 3D medical imaging remains…
Medal S: Spatio-Textual Prompt Model for Medical Segmentation
Pengcheng Shi, Jiawei Chen, Jiaqi Liu +3
We introduce Medal S, a medical segmentation foundation model that supports native-resolution spatial and textual prompts within an end-to-end trainable framework. Unlike text-only…
Addressing Domain Shift via Imbalance-Aware Domain Adaptation in Embryo Development Assessment
Lei Li, Xinglin Zhang, Jun Liang +1
Deep learning models in medical imaging face dual challenges: domain shift, where models perform poorly when deployed in settings different from their training environment, and cla…