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Classification and Recognition of Ovarian Cells Based on Two-Dimensional Light Scattering Technology

机译:基于二维光散射技术的卵巢细胞分类与识别

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摘要

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.
机译:卵巢癌是一个非常阴险的恶性肿瘤。 为了早期检测卵巢癌细胞,卵巢癌细胞的分类和识别主要由二维光散射技术研究。 首先,基于单模光纤照明的单细胞二维光散射模式采集平台被设计为收集卵巢癌细胞和正常卵巢细胞的一定数量的二维光散射模式。 然后,用于提取二维光散射图案的剃刮各向异性特征的猪(取向梯度的直方图)。 结果表明,二维光散射技术的分类和鉴定的准确性为90.81%,表明癌细胞的特异性和正常细胞的特征可以通过二维光散射技术来表征。

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