酿酒酵母单细胞形态参数精准提取算法的研究

An Algorithm to Accurately Extract The Morphological Parameter of Budding Yeast Cells

酿酒酵母是一种常用于细胞衰老研究的模式细胞。在细胞衰老研究中,以高通量微流控芯片作为酵母细胞动力学分析平台,实验者可以捕获并连续培养酵母单细胞,并通过时序显微成像监测其生长及衰老过程。为了自动化分析大量酵母细胞实验获得的大量图像,本文提出了一种基于MATLAB的图像处理算法,用于从时序显微图像中提取酿酒酵母单细胞的形态学参数,如母细胞截面面积。该算法融合了Hough变换、魔棒函数和分水岭算法、形态学膨胀等步骤,具有高效、精确等优点。此外,本文还应用该算法提取了酵母母细胞在衰老过程中的截面面积,验证了母细胞截面面积的动态变化与其复制寿命具有相关性。

The budding yeast, Saccharomyces cerevisiae, as a typical model organism, is often used for cell aging studies, where high-throughput microfluidic devices have become important platforms to analyze cell dynamics of yeast. In such devices, single budding yeast cells are usually captured and continuously cu\ured in dedicated microstructures, and then time-lapse microscopic imaging is performed to monitor cell growth and aging of immobilized cells. In this work, a MATLAB-based image processing algorithm is proposed for extracting morphological parameter(i.e.,cell cross-sectional area)of budding yeast cells from time-lapse images. This efficient and accurate algorithm integrated Hough transform, magic wand function, watershed algorithm, and morphological dilation. In addition, the algorithm was utilized to investigate the cross-sectional area of mother cells during aging, demonstrating a correlation between mother cell size and replicative lifespan of budding(RLS)yeast.