Abstract
Ovarian cancer is a very insidious malignant tumor. In order to detect ovarian cancer cells early, the classification and recognition of ovarian cancer cells is mainly studied by two-dimensional light scattering technology. Firstly, a single-cell two-dimensional light scattering pattern acquisition platform based on single-mode optical fiber illumination is designed to collect a certain number of two-dimensional light scattering patterns of ovarian cancer cells and normal ovarian cells. Then, the HOG (Histogram of Oriented Gradient) algorithm is used to extract shaving anisotropy feature of two-dimensional light scattering pattern. The results show that the accuracy of classification and identification of ovarian cancer cells by two-dimensional light scattering technology is 90.81%, which suggests that the specificity of cancer cells and normal cells can be characterized by two-dimensional light scattering technology.
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