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An Image Segmentation Method for Quasi-circular Immune Cells

机译:准圆形免疫细胞的图像分割方法

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摘要

Aiming at the characteristic of actual quasi-circular immune cell images, this paper presents the method of quasi-circular immune cell images segmentation based on Otsu threshold and thinning algorithm. The image is first converted color space form RGB to YIQ. Then the image is segmented by Otsu threshold algorithm. And then the erosion and dilation of morphological filter are used to process the image. Finally, the Zhang-Suen thinning algorithm is employed to extract the cell’s skeleton, which is the center of the quasi-circular immune cell. According to the thinning times, we can obtain the radius value of the quasi-circular immune cell, and the overlapping quasi-circular immune cells are separated. Experimental results show this method works successfully in the segmentation of quasi-circular immune cell images.
机译:旨在瞄准实际准圆形免疫细胞图像的特征,本文提出了基于OTSU阈值和稀疏算法的准圆形免疫细胞图像分割方法。图像是首先将颜色空间形式RGB转换为yiq。然后通过OTSU阈值算法分段图像。然后使用形态过滤器的侵蚀和扩张来处理图像。最后,采用张素稀薄算法来提取细胞的骨架,其是准圆形免疫细胞的中心。根据稀释时间,我们可以获得准圆形免疫细胞的半径值,并且分离重叠的准圆形免疫细胞。实验结果表明,该方法成功地在准圆形免疫细胞图像的分割中成功地工作。

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