114 citations · 147 across the 14 of their papers we have counts for
14 papers
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…
Abn-BLIP: Abnormality-aligned Bootstrapping Language-Image Pre-training for Pulmonary Embolism Diagnosis and Report Generation from CTPA
Zhusi Zhong, Yuli Wang, Lulu Bi +13
Medical imaging plays a pivotal role in modern healthcare, with computed tomography pulmonary angiography (CTPA) being a critical tool for diagnosing pulmonary embolism and other t…
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…
Infrared and Visible Image Fusion with Hierarchical Human Perception
Guang Yang, Jie Li, Xin Liu +2
Image fusion combines images from multiple domains into one image, containing complementary information from source domains. Existing methods take pixel intensity, texture and high…
Pulmonary Embolism Mortality Prediction Using Multimodal Learning Based on Computed Tomography Angiography and Clinical Data
Zhusi Zhong, Helen Zhang, Fayez H. Fayad +12
Purpose: Pulmonary embolism (PE) is a significant cause of mortality in the United States. The objective of this study is to implement deep learning (DL) models using Computed Tomo…
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…
Region-specific Risk Quantification for Interpretable Prognosis of COVID-19
Zhusi Zhong, Jie Li, Zhuoqi Ma +7
The COVID-19 pandemic has strained global public health, necessitating accurate diagnosis and intervention to control disease spread and reduce mortality rates. This paper introduc…
SMC-UDA: Structure-Modal Constraint for Unsupervised Cross-Domain Renal Segmentation
Zhusi Zhong, Jie Li, Lulu Bi +6
Medical image segmentation based on deep learning often fails when deployed on images from a different domain. The domain adaptation methods aim to solve domain-shift challenges, b…
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…
A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation
Zhenxi Zhang, Jie Li, Zhusi Zhong +2
3D image segmentation is one of the most important and ubiquitous problems in medical image processing. It provides detailed quantitative analysis for accurate disease diagnosis, a…
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…