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

  • Systems-Level Quality Improvement
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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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Authors and Affiliations

  1. Department of Gynaecology and Obstetrics, Zoucheng People’s Hospital, No.59 Qianquan Road, Zoucheng, 273500, Shandong, China

    Qi Chen & Jianling Zhang

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  1. Qi Chen
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  2. Jianling Zhang
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Correspondence to Jianling Zhang.

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Author Qi Chen declares that he has no conflict of interest. Author Jianling Zhang declares that he has no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Chen, Q., Zhang, J. Classification and Recognition of Ovarian Cells Based on Two-Dimensional Light Scattering Technology. J Med Syst 43, 127 (2019). https://doi.org/10.1007/s10916-019-1211-y

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  • DOI: https://doi.org/10.1007/s10916-019-1211-y

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