4 citations · 20 across the 23 of their papers we have counts for
7 papers · 1 filter
Cross-Fundus Transformer for Multi-modal Diabetic Retinopathy Grading with Cataract
Fan Xiao, Junlin Hou, Ruiwei Zhao +5
Diabetic retinopathy (DR) is a leading cause of blindness worldwide and a common complication of diabetes. As two different imaging tools for DR grading, color fundus photography (…
MOSMOS: Multi-organ segmentation facilitated by medical report supervision
Weiwei Tian, Xinyu Huang, Junlin Hou +6
Owing to a large amount of multi-modal data in modern medical systems, such as medical images and reports, Medical Vision-Language Pre-training (Med-VLP) has demonstrated incredibl…
Concept-Attention Whitening for Interpretable Skin Lesion Diagnosis
Junlin Hou, Jilan Xu, Hao Chen
The black-box nature of deep learning models has raised concerns about their interpretability for successful deployment in real-world clinical applications. To address the concerns…
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…
Retrieval-Augmented Egocentric Video Captioning
Jilan Xu, Yifei Huang, Junlin Hou +4
Understanding human actions from videos of first-person view poses significant challenges. Most prior approaches explore representation learning on egocentric videos only, while ov…