We develop a single-mode fiber-based cytometer for the obtaining of two-dimensional (2D) light scattering patterns from static single cells. Anisotropy of the 2D light scattering patterns of single cells from ovarian cancer and normal cell lines is investigated by histograms of oriented gradients (HOG) method. By analyzing the HOG descriptors with support vector machine, an accuracy rate of 92.84% is achieved for the automatic classification of these two kinds of label-free cells. The 2D light scattering anisotropy cytometry combined with machine learning may provide a label-free, automatic method for screening of ovarian cancer cells, and other types of cells. © 2019 International Society for Advancement of Cytometry.

中文翻译：

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二维光散射各向异性细胞术，用于通过机器学习对卵巢癌细胞进行无标签分类。

我们开发了一种基于单模光纤的细胞仪，用于从静态单细胞中获得二维（2D）光散射图案。通过定向梯度直方图（HOG）方法研究来自卵巢癌和正常细胞系的单细胞的二维光散射模式的各向异性。通过使用支持向量机分析HOG描述符，对这两种无标记细胞进行自动分类的准确率达到92.84％。与机器学习相结合的2D光散射各向异性细胞术可以提供一种无标记的自动方法来筛选卵巢癌细胞和其他类型的细胞。©2019国际细胞计数学会。