3 citations · 6 across the 8 of their papers we have counts for
15 papers
Dual Semantic-Aware Network for Noise Suppressed Ultrasound Video Segmentation
Ling Zhou, Runtian Yuan, Yi Liu +3
Ultrasound imaging is a prevalent diagnostic tool known for its simplicity and non-invasiveness. However, its inherent characteristics often introduce substantial noise, posing con…
Advancing Lung Disease Diagnosis in 3D CT Scans
Qingqiu Li, Runtian Yuan, Junlin Hou +4
To enable more accurate diagnosis of lung disease in chest CT scans, we propose a straightforward yet effective model. Firstly, we analyze the characteristics of 3D CT scans and re…
AOR: Anatomical Ontology-Guided Reasoning for Medical Large Multimodal Model in Chest X-Ray Interpretation
Qingqiu Li, Zihang Cui, Seongsu Bae +8
Chest X-rays (CXRs) are the most frequently performed imaging examinations in clinical settings. Recent advancements in Large Multimodal Models (LMMs) have enabled automated CXR in…
An Empirical Analysis of Uncertainty in Large Language Model Evaluations
Qiujie Xie, Qingqiu Li, Zhuohao Yu +3
As LLM-as-a-Judge emerges as a new paradigm for assessing large language models (LLMs), concerns have been raised regarding the alignment, bias, and stability of LLM evaluators. Wh…
Text-Promptable Propagation for Referring Medical Image Sequence Segmentation
Runtian Yuan, Mohan Chen, Jilan Xu +6
Referring Medical Image Sequence Segmentation (Ref-MISS) is a novel and challenging task that aims to segment anatomical structures in medical image sequences (\emph{e.g.} endoscop…
FineMedLM-o1: Enhancing Medical Knowledge Reasoning Ability of LLM from Supervised Fine-Tuning to Test-Time Training
Hongzhou Yu, Tianhao Cheng, Yingwen Wang +6
Recent advancements in large language models (LLMs) have shown promise in medical applications such as disease diagnosis and treatment planning. However, most existing medical LLMs…