7 citations · 8 across the 10 of their papers we have counts for
4 papers · 1 filter
Co-Evidential Fusion with Information Volume for Medical Image Segmentation
Yuanpeng He, Lijian Li, Tianxiang Zhan +3
Although existing semi-supervised image segmentation methods have achieved good performance, they cannot effectively utilize multiple sources of voxel-level uncertainty for targete…
Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation
Lijian Li, Yuanpeng He, Chi-Man Pun
Recently, prototype learning has emerged in semi-supervised medical image segmentation and achieved remarkable performance. However, the scarcity of labeled data limits the express…
Mutual Evidential Deep Learning for Medical Image Segmentation
Yuanpeng He, Yali Bi, Lijian Li +3
Existing semi-supervised medical segmentation co-learning frameworks have realized that model performance can be diminished by the biases in model recognition caused by low-quality…
Multi-Prototype Embedding Refinement for Semi-Supervised Medical Image Segmentation
Yali Bi, Enyu Che, Yinan Chen +2
Medical image segmentation aims to identify anatomical structures at the voxel-level. Segmentation accuracy relies on distinguishing voxel differences. Compared to advancements ach…