activity
20232026
most citedAnatomical Structure-Guided Medical Vision-Language Pre-training

1 citations · 1 across the 10 of their papers we have counts for

collaborators

11 papers

eess.IV2026

Clinical Priors Guided Lung Disease Detection in 3D CT Scans

Kejin Lu, Jianfa Bai, Qingqiu Li +5

Accurate classification of lung diseases from chest CT scans plays an important role in computer-aided diagnosis systems. However, medical imaging datasets often suffer from severe…

eess.IV2026

Vision-Language Model Based Multi-Expert Fusion for CT Image Classification

Jianfa Bai, Kejin Lu, Runtian Yuan +5

Robust detection of COVID-19 from chest CT remains challenging in multi-institutional settings due to substantial source shift, source imbalance, and hidden test-source identities.…

cs.CV2025

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…

eess.IV2025

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…

eess.IV2025

Multi-Source COVID-19 Detection via Variance Risk Extrapolation

Runtian Yuan, Qingqiu Li, Junlin Hou +4

We present our solution for the Multi-Source COVID-19 Detection Challenge, which aims to classify chest CT scans into COVID and Non-COVID categories across data collected from four…

cs.CV2025

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…

cs.CV2025

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…

eess.IV2024

Advancing COVID-19 Detection in 3D CT Scans

Qingqiu Li, Runtian Yuan, Junlin Hou +4

To make a more accurate diagnosis of COVID-19, we propose a straightforward yet effective model. Firstly, we analyse the characteristics of 3D CT scans and remove the non-lung part…

eess.IV2024

Domain Adaptation Using Pseudo Labels for COVID-19 Detection

Runtian Yuan, Qingqiu Li, Junlin Hou +4

In response to the need for rapid and accurate COVID-19 diagnosis during the global pandemic, we present a two-stage framework that leverages pseudo labels for domain adaptation to…

cs.CV2024★ 1 cited

Anatomical Structure-Guided Medical Vision-Language Pre-training

Qingqiu Li, Xiaohan Yan, Jilan Xu +6

Learning medical visual representations through vision-language pre-training has reached remarkable progress. Despite the promising performance, it still faces challenges, i.e., lo…

cs.CV2023

Enhanced Knowledge Injection for Radiology Report Generation

Qingqiu Li, Jilan Xu, Runtian Yuan +5

Automatic generation of radiology reports holds crucial clinical value, as it can alleviate substantial workload on radiologists and remind less experienced ones of potential anoma…