Xueyu Liu, Rui Wang, Yexin Lai, Yongfei Wu, Hangbei Cheng, Yuanyue Lu, Jianan Zhang, Ning Hao, Chenglong Ban, Yanru Wang, Shuqin Tang, Yuxuan Yang, Ming Li, Xiaoshuang Zhou, Wen Zheng
Accurately diagnosing chronic kidney disease requires pathologists to assess the structure of multiple tissues under different stains, a process that is timeconsuming and labor-intensive. Current AI-based methods for automatic structure assessment, like segmentation, often demand extensive manual annotation and focus on single stain domain. To address these challenges, we introduce MSMTSeg, a generative self-supervised meta-learning framework for multi-stained multi-tissue segmentation in renal biopsy whole slide images (WSIs)...
March 25, 2024: IEEE Journal of Biomedical and Health Informatics