Strbkova Lenka, Zicha Daniel, Vesely Pavel, Chmelik Radim
Brno University of Technology, Central European Institute of Technology, Brno, Czech Republic.
Brno University of Technology, Institute of Physical Engineering, Faculty of Mechanical Engineering,, Czech Republic.
J Biomed Opt. 2017 Aug;22(8):1-9. doi: 10.1117/1.JBO.22.8.086008.
In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.
在过去几年中，通过机器学习对细胞进行分类在生物学中已变得频繁使用。然而，大多数方法基于形态测量（MO）特征，这些特征在细胞质量方面并非定量的。这可能导致分类准确率较低。在此，我们研究相干控制全息显微镜在细胞形态分类中实现定量相位成像的潜在贡献。我们将我们的方法与基于MO特征的常用方法进行比较。我们在对营养缺乏的癌组织细胞进行的实验中测试了这两种分类方法，同时采用了几种监督机器学习算法。当使用定量相位特征时，大多数分类器表现出更高的性能。基于这些结果，可以得出结论，定量相位特征在提高分类性能方面发挥了重要作用。该方法对于以自动化方式完善活细胞监测可能会有宝贵帮助。我们相信，作为定量相位成像工具的相干控制全息显微镜，为准确自动分析活细胞行为提供了所有前提条件，同时能够进行具有足够对比度和高时空相位灵敏度的无创无标记成像。
