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20242026
most citedQMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis

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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.…

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…

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…