4 papers · 1 filter
MSLAU-Net: A Hybrid CNN-Transformer Network for Medical Image Segmentation
Libin Lan, Yanxin Li, Xiaojuan Liu +4
Accurate medical image segmentation allows for the precise delineation of anatomical structures and pathological regions, which is essential for treatment planning, surgical naviga…
FullTransNet: Full Transformer with Local-Global Attention for Video Summarization
Libin Lan, Lu Jiang, Tianshu Yu +2
Video summarization aims to generate a compact, informative, and representative synopsis of raw videos, which is crucial for browsing, analyzing, and understanding video content. D…
KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level
Ruining Deng, Tianyuan Yao, Yucheng Tang +44
Chronic kidney disease (CKD) is a major global health issue, affecting over 10% of the population and causing significant mortality. While kidney biopsy remains the gold standard f…
BRAU-Net++: U-Shaped Hybrid CNN-Transformer Network for Medical Image Segmentation
Libin Lan, Pengzhou Cai, Lu Jiang +3
Accurate medical image segmentation is essential for clinical quantification, disease diagnosis, treatment planning and many other applications. Both convolution-based and transfor…