基于区域生长的细胞生长汇合度计算

Calculation of Cell Growth Confluence Based on Region growth

摘要: 细胞生长汇合度一般指细胞贴壁并且完全舒展之后，细胞所占的面积的占培养表面面积的百分比，它作为细胞体外培养环节中的主要参数，对后续的传代培养有着重要影响。传统计算细胞生长汇合度主要的方法通过人工观察，根据经验值判断，对结果有较大的误差，不适用于大规模批量生产。为此本文采用数字图像处理技术代替人工，提出了一种基于区域生长的细胞生长汇合度计算方法。首先，采用改进的高斯-拉普拉斯算子对图像预处理增强对比度；其次，应用均值漂移算法将细胞区域和非细胞区域分离；最后，使用数学形态学操作过滤面积较小的空白区域，进而实现细胞区域与背景的有效分离，得到准确细胞的生长汇合度。本文通过实验室采集的Hela细胞数据集与人工方式相比较，保证了准确性的同时提高了计算速度，在批量生产过程中有效替代传统的人工方法进行细胞生长汇合度计算。

Abstract: Cell growth confluence is the main parameter in the in vitro culture of cells, which has an im-portant impact on subsequent subculture. The main method for calculating the cell growth con-vergence degree by manual observation is judged according to the empirical value, and the result has a large error, which is not suitable for large-scale mass production. The development of digital image processing is largely based on the calculation of cell growth convergence to improve efficiency and objective accuracy. To this end, this paper proposes a method for calculating the cell growth convergence based on region growth. First, the improved Gauss-Laplacian operator is used to enhance the contrast of the image preprocessing; secondly, the mean shift algorithm is used to separate the cell region from the non-cell region; finally, the mathematical region is used to filter the blank region with smaller area. In turn, the effective separation of the cell region from the background is achieved, and the growth confluence of the cells is obtained accurately. In this paper, the algorithm is applied to the image of cells collected in the laboratory and the network, and the effectiveness of the algorithm is verified by experiments, which effectively replaces the traditional artificial method for cell growth convergence calculation.