activity
20242026
most citedAbn-BLIP: Abnormality-aligned Bootstrapping Language-Image Pre-training for Pulmonary Embolism Diagnosis and Report Generation from CTPA

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2026

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…

eess.IV2026

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…

cs.CV2025★ 1 cited

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…

eess.IV2024

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…

cs.CV2024

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…

eess.IV2024★ 1 cited

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…

cs.CV2024

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…