4 papers
Multimodal Medical Endoscopic Image Analysis via Progressive Disentangle-aware Contrastive Learning
Junhao Wu, Yun Li, Junhao Li +4
Accurate segmentation of laryngo-pharyngeal tumors is crucial for precise diagnosis and effective treatment planning. However, traditional single-modality imaging methods often fal…
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image Segmentation
Lingcong Cai, Yun Li, Xiaomao Fan +3
The segmentation of endoscopic images plays a vital role in computer-aided diagnosis and treatment. The advancements in deep learning have led to the employment of numerous models…
3D-LSPTM: An Automatic Framework with 3D-Large-Scale Pretrained Model for Laryngeal Cancer Detection Using Laryngoscopic Videos
Meiyu Qiu, Yun Li, Wenjun Huang +4
Laryngeal cancer is a malignant disease with a high morality rate in otorhinolaryngology, posing an significant threat to human health. Traditionally larygologists manually visual-…
Rethinking Radiology Report Generation via Causal Inspired Counterfactual Augmentation
Xiao Song, Jiafan Liu, Yun Li +3
Radiology Report Generation (RRG) draws attention as a vision-and-language interaction of biomedical fields. Previous works inherited the ideology of traditional language generatio…