Multi-dimensional Fusion and Consistency for Semi-supervised Medical Image Segmentation

Yixing Lu,Zhaoxin Fan,Min Xu

arXiv (Cornell University)(2023)

引用 0|浏览10
暂无评分
摘要
In this paper, we introduce a novel semi-supervised learning framework tailored for medical image segmentation. Central to our approach is the innovative Multi-scale Text-aware ViT-CNN Fusion scheme. This scheme adeptly combines the strengths of both ViTs and CNNs, capitalizing on the unique advantages of both architectures as well as the complementary information in vision-language modalities. Further enriching our framework, we propose the Multi-Axis Consistency framework for generating robust pseudo labels, thereby enhancing the semi-supervised learning process. Our extensive experiments on several widely-used datasets unequivocally demonstrate the efficacy of our approach.
更多
查看译文
关键词
image segmentation,fusion,multi-dimensional,semi-supervised
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要