1 citations · 1 across the 9 of their papers we have counts for
10 papers
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…
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.…
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…
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…
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…
EgoExo-Gen: Ego-centric Video Prediction by Watching Exo-centric Videos
Jilan Xu, Yifei Huang, Baoqi Pei +6
Generating videos in the first-person perspective has broad application prospects in the field of augmented reality and embodied intelligence. In this work, we explore the cross-vi…
QMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis
Junlin Hou, Jilan Xu, Rui Feng +1
Due to the complexity of medical image acquisition and the difficulty of annotation, medical image datasets inevitably contain noise. Noisy data with wrong labels affects the robus…
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…
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…