Semi supervised segmentation and graph-based tracking of 3D nuclei in time-lapse microscopy

2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)(2021)

引用 6|浏览9
暂无评分
摘要
We propose a novel weakly supervised method to improve the boundary of the 3D segmented nuclei utilizing an over-segmented image. This is motivated by the observation that current state-of-the-art deep learning methods do not result in accurate boundaries when the training data is weakly annotated. Towards this, a 3DU-Net is trained to get the centroid of the nuclei and integrated with a simple li...
更多
查看译文
关键词
Deep learning,Image segmentation,Three-dimensional displays,Microscopy,Pipelines,Clustering algorithms,Training data
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