A tower layered algorithm for medical image segmentation

机译：一种塔分层算法，用于医学图像分割

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摘要

This paper proposes an algorithm named Tower Layered FCM to improve the traditional FCM method. A Tower layered structure with a constraint is added into the objective function and pixel's neighbor information is rational used. The Tower layered structure can speed up the algorithm and constraint the subordinate degree of pixels. So the subordinate degree of clustering center is made more reasonable. The experimental result shows that the new algorithm can save detail image information and it is more efficient than the traditional FCM.

机译：本文提出了一种名为Tower分层FCM的算法来提高传统的FCM方法。具有约束的塔分层结构被添加到目标函数中，并且像素的邻居信息使用是合理的。塔分层结构可以加快算法并约束从属像素程度。因此聚类中心的从属程度更合理。实验结果表明，新算法可以节省详细图像信息，并且比传统的FCM更有效。

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《International Conference on computer science education》|2015年||共4页
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作者
Tao Jia; Huang Run-hua;
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正文语种
中图分类计算技术、计算机技术;
关键词
Fuzzy C-means algorithm; image segmentation; spatial information; tower structure;

机译：模糊C型算法;图像分割;空间信息;塔结构;

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4. A tower layered algorithm for medical image segmentation [C] . Tao Jia, Huang Run-hua International Conference on computer science education . 2015

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A tower layered algorithm for medical image segmentation

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