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Method for cell image segmentation based on bilateral filtering and CV Model

机译:基于双边滤波和CV模型的细胞图像分割方法

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摘要

Objectives: Change the initial value of CV model to achieve the purpose of cell image segmentation fast and accurately. Material and methods: This paper selects slice image of cervical-cancer cells under a microscope as experimental materials. First, the original image is bilateral filtered and then the image is preprocessed using Otsu method to get the rough contour of cytoplasm. Then use Otsu method twice on the cytoplasm to get the rough contour of nucleus. Finally, regard the preprocessed results as the initial value of CV model and evolve the curve with level set method to obtain the final contour. Results: This proposed method costs 17.057s and the iterations are 50, the contour is accurate. Meanwhile, the existed method costs 45.329s and the iterations are 90 and it doesn't iterate to the accurate result. Conclusions: It can obtain accurate cell contour fast regarding the preprocessed result of bilateral filtering and Otsu method as the initial value of CV model.
机译:目的:改变CV模型的初始值,以达到快速准确地进行细胞图像分割的目的。材料和方法:本文选择显微镜下宫颈癌细胞的切片图像作为实验材料。首先,对原始图像进行双边滤波,然后使用Otsu方法对图像进行预处理,以获取细胞质的粗糙轮廓。然后在细胞质上使用大津法两次以得到细胞核的粗糙轮廓。最后,将预处理后的结果作为CV模型的初始值,并用水平集方法对曲线进行演化,得到最终轮廓。结果:该方法的成本为17.057s,迭代次数为50,轮廓准确。同时,现有方法的成本为45.329s,迭代次数为90,并且不会迭代到准确的结果。结论:以双边滤波和大津法的预处理结果作为CV模型的初始值,可以快速获得准确的细胞轮廓。

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