首页> 外文会议>Pattern Recognition, 2009. CCPR 2009 >Stomach Epidermis Tumor Cell Segmentation Based on the Maximization of Mutual Information in Effective Information
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Stomach Epidermis Tumor Cell Segmentation Based on the Maximization of Mutual Information in Effective Information

机译:基于有效信息互信息最大化的胃表皮肿瘤细胞分割

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In the complex stomach epidermis tumor cells, the traditional segmentation algorithms such as the K-means clustering algorithm and the simple threshold segmentation algorithm are unable to get satisfactory results. The relaxation iterative segmentation algorithm can segment the cell clearly, but it wastes a lot of time and the execution efficiency is very low. In this paper the authors propose a new segmentation algorithm based on the maximization of Mutual information in effective information, in which to find the optimal threshold values to segment the stomach epidermis tumor cells.
机译:在复杂的胃表皮肿瘤细胞中,传统的分割算法如K均值聚类算法和简单的阈值分割算法无法获得满意的效果。松弛迭代分割算法可以清晰地对单元进行分割,但是浪费很多时间,执行效率很低。在本文中,作者提出了一种基于有效信息中互信息最大化的新分割算法,该算法寻找最佳阈值来分割胃表皮肿瘤细胞。

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