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Adaptive Thresholding Based Cell Segmentation for Cell-Destruction Activity Verification

机译:基于自适应阈值的细胞销毁活动验证的细胞分段

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An adaptive thresholding method used to distinguish cell boundaries in a given image is presented in this paper. A preprocessing step involves low pass filtering of the image to remove high frequency noise seen in the image. This image is now adaptively thresholded to create a binary image. The bright regions are further analyzed based on their geometrical descriptors such as area and form factor to classify them as cell or non-cell regions. Two sets of images, pulsed and non-pulsed, are available, which can be compared to determine the efficiency of the pulsing. Results for automatic segmentation are compared with those of manually obtained values to determine its efficiency.
机译:本文介绍了用于区分给定图像中的小区边界的自适应阈值方法。预处理步骤涉及图像的低通滤波以去除图像中看到的高频噪声。现在自适应地阈值为阈值以创建二进制图像。基于它们的几何描述符(例如区域和形状因子)进一步分析明亮区域,以将它们分类为细胞或非小区区域。有两组图像,脉冲和非脉冲可用,可以进行比较以确定脉冲的效率。将自动分割的结果与手动获得的值进行比较以确定其效率。

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