摘要
对于显微注射过程中的细胞质分割问题,传统水平集模型无法在多个目标连成一体的情况下分割出细胞质,且分割速度慢.为此,文中首先依据形状差异性特点获取细胞和注射针的联合轮廓,而后结合变分水平集理论增加边缘约束条件,改进能量泛函模型,实现对细胞质的完整分割,同时大幅提升水平集收敛速度.实验结果表明,文中算法可以快速实现细胞质的独立分割,同时避免对其他目标的错误分割.
So far as the cytoplasm segmentation in the process of cell microinjection is concerned,the traditional level set models can not directly segment cytoplasm from multiple adhered targets. Additionally,they are slow in segmentation. In order to solve these problems,a new cell segmentation method based on variation level set is proposed. In this method,the joint contour of cell and injection pipette is acquired according to the difference in shape. Then,by combining the variation level set theory,an extra edge constraint is added to improve the energy functional model. A complete cell segmentation is thus achieved and the convergence speed of the variation level set is significantly improved. Experimental results indicate that the proposed method helps to perform the independent cytoplasm segmentation rapidly and at the same time avoid wrong segmentation of other targets.
出处
《华南理工大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2014年第3期15-20,34,共7页
Journal of South China University of Technology(Natural Science Edition)
基金
广东省科技厅国际合作项目(2012B050600011)
广东高校国际科技合作项目(粤教科函[2010]119)
高等学校博士学科点专项科研基金新教师课题(20120172120032)
广州市科信局国际合作项目(2012J5100001)
关键词
变分水平集
自动细胞注射
细胞分割
图像增强
variation level set
automatic cell injection
cell segmentation
image enhancement