collaborators

5 papers

cs.LG2025

Hyperbolic Continuous Structural Entropy for Hierarchical Clustering

Guangjie Zeng, Hao Peng, Angsheng Li +5

Hierarchical clustering is a fundamental machine-learning technique for grouping data points into dendrograms. However, existing hierarchical clustering methods encounter two prima…

cs.CV2025

CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images

Dongdong Meng, Sheng Li, Hao Wu +4

Accurate automatic medical image segmentation relies on high-quality, dense annotations, which are costly and time-consuming. Weakly supervised learning provides a more efficient a…

cs.CV2025

Semi-Supervised Multi-Modal Medical Image Segmentation for Complex Situations

Dongdong Meng, Sheng Li, Hao Wu +2

Semi-supervised learning addresses the issue of limited annotations in medical images effectively, but its performance is often inadequate for complex backgrounds and challenging t…

cs.CV2025

Query Nearby: Offset-Adjusted Mask2Former enhances small-organ segmentation

Xin Zhang, Dongdong Meng, Sheng Li

Medical segmentation plays an important role in clinical applications like radiation therapy and surgical guidance, but acquiring clinically acceptable results is difficult. In rec…

cs.CV2024

GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation

Mengzhu Wang, Jiao Li, Houcheng Su +3

Semi-supervised learning (SSL) has made notable advancements in medical image segmentation (MIS), particularly in scenarios with limited labeled data and significantly enhancing da…