医学图像分割中的模糊聚类技术

M. Tabakov
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引用次数: 37

摘要

医学图像分割的主要目的是根据一些输入特征或专家知识提取和表征解剖结构。本文提出了一种基于模糊相似关系的模糊聚类分割方法。所考虑的关系是根据欧几里得度规定义的。介绍了一种基于模糊相似关系的图像分割算法。为了说明得到的分割过程,考虑了一些计算机断层成像的例子。本文还给出了经典模糊c均值聚类算法的一些结果,以供比较
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fuzzy Clustering Technique for Medical Image Segmentation
The main objective of medical image segmentation is to extract and characterise anatomical structures with respect to some input features or expert knowledge. This paper describes a way of medical image segmentation using an appropriately defined fuzzy clustering method based on a fuzzy similarity relation. The considered relation is defined in terms of the Euclidean metric. A fuzzy similarity relation-based image segmentation algorithm is also introduced. To illustrate the obtained segmentation process some examples of computed tomography imaging are considered. Some results, using the classical fuzzy c-means clustering algorithm are also presented, for a comparison purpose
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