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Detection Technique of Squamous Epithelial Cells in Sputum Slide Images using Image Processing Analysis

机译:图像处理分析在痰标本图像中鳞状上皮细胞的检测技术

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摘要

A good quality sputum is important to detect diseases. The presence of squamous epithelial cells (SEC) in sputum slide images is important to determine the quality of sputum. The presence of overlapping SEC in sputum slide images causes the process become complicated and tedious. Therefore this paper discusses on technique of detection and summation for Squamous Epithelial Cell (SEC) in sputum slide image. We addressed the detection problem by combining K-means and color thresholding algorithm. The design of aided system is evaluated using 200 images and the proposed technique is capable to detect and count each SEC from overlapping SEC image. Total of 200 images were clustered to 10 groups, labelled as Group Cell 1 to group Cell 10 that correspond to the number of cells in the image. Therefore, each group will contain 20 images. The accuracy of the algorithm to detect SEC was also measured, and results show that in 91% which provides a correct SEC detection and summation.
机译:高质量的痰对于检测疾病很重要。痰玻片图像中鳞状上皮细胞(SEC)的存在对于确定痰的质量很重要。痰玻片图像中重叠的SEC的存在使该过程变得复杂而乏味。因此,本文讨论了痰标本图像中鳞状上皮细胞(SEC)的检测和求和技术。我们通过结合K均值和颜色阈值算法解决了检测问题。辅助系统的设计使用200张图像进行评估,所提出的技术能够从重叠的SEC图像中检测和计数每个SEC。将总共​​200张图像聚类为10个组,分别标记为“组单元1”到“组单元10”,这些组与图像中的单元数相对应。因此,每个组将包含20张图像。还测量了算法检测SEC的准确性,结果表明91%的算法可提供正确的SEC检测和求和。

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