114 citations · 147 across the 14 of their papers we have counts for
8 papers · 1 filter
Reliability Stress Tests and Decision-Time Routing for Chest X-ray Vision-Language Models
Xinye Yang, Zhusi Zhong, Scott Collins +3
Medical vision-language model (VLM) evaluation is sensitive to workflow design, prompting strategy, and benchmark construction, yet most studies treat these factors in isolation. W…
Confidence-Gated Cloud-Edge Cascade Triage via Variational Risk Minimization for Medical Imaging
Xinye Yang, Zhusi Zhong, Scott Collins +7
Emergency chest X-ray (CXR) triage has a structural modality gap: reports arrive after triage decisions, yet multimodal foundation models require image-text inputs. We present Vari…
A multitask framework for automated interpretation of multi-frame right upper quadrant ultrasound in clinical decision support
Haiman Guo, Cheng-Yi Li, Yuli Wang +26
Ultrasound is a cornerstone of emergency and hepatobiliary imaging, yet its interpretation remains highly operator-dependent and time-sensitive. Here, we present a multitask vision…
Optimizing Prompt Strategies for SAM: Advancing lesion Segmentation Across Diverse Medical Imaging Modalities
Yuli Wang, Victoria Shi, Wen-Chi Hsu +9
Purpose: To evaluate various Segmental Anything Model (SAM) prompt strategies across four lesions datasets and to subsequently develop a reinforcement learning (RL) agent to optimi…
Structural Entities Extraction and Patient Indications Incorporation for Chest X-ray Report Generation
Kang Liu, Zhuoqi Ma, Xiaolu Kang +5
The automated generation of imaging reports proves invaluable in alleviating the workload of radiologists. A clinically applicable reports generation algorithm should demonstrate i…
Multi-modality Regional Alignment Network for Covid X-Ray Survival Prediction and Report Generation
Zhusi Zhong, Jie Li, John Sollee +7
In response to the worldwide COVID-19 pandemic, advanced automated technologies have emerged as valuable tools to aid healthcare professionals in managing an increased workload by…
Collaborative Boundary-aware Context Encoding Networks for Error Map Prediction
Zhenxi Zhang, Chunna Tian, Jie Li +3
Medical image segmentation is usually regarded as one of the most important intermediate steps in clinical situations and medical imaging research. Thus, accurately assessing the s…
An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms
Zhusi Zhong, Jie Li, Zhenxi Zhang +2
Cephalometric tracing method is usually used in orthodontic diagnosis and treatment planning. In this paper, we propose a deep learning based framework to automatically detect anat…