5 papers · 1 filter
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…
SAM-Swin: SAM-Driven Dual-Swin Transformers with Adaptive Lesion Enhancement for Laryngo-Pharyngeal Tumor Detection
Jia Wei, Yun Li, Xiaomao Fan +4
Laryngo-pharyngeal cancer (LPC) is a highly lethal malignancy in the head and neck region. Recent advancements in tumor detection, particularly through dual-branch network architec…
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-…
SAM-FNet: SAM-Guided Fusion Network for Laryngo-Pharyngeal Tumor Detection
Jia Wei, Yun Li, Meiyu Qiu +3
Laryngo-pharyngeal cancer (LPC) is a highly fatal malignant disease affecting the head and neck region. Previous studies on endoscopic tumor detection, particularly those leveragin…
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…