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磁共振脑图像模糊聚类分割中的参数选择问题研究
The Study of Parameter Choice in Fuzzy Clustering Segmentation for MRI Brain Images
【摘要】 作为一种重要的分类器,模糊聚类技术在磁共振图像的分割中已经得到了成功的应用,并成为了一种有效的磁共振图像的分割工具。尽管如此,模糊聚类技术在图像分割中仍然存在着一些不确定的因素,集中表现在模糊聚类的参数选择方面,如模糊指数、聚类数和距离范数的选择。这些参数的选择问题直接影响模糊聚类的速度和精度。本文对这些问题进行了系统地研究和讨论,并针对磁共振脑图像,给出了参数选择方案。
【Abstract】 As an important classifier, fuzzy clustering technique has been widely used in segmentation of MRI image and became an effective segmentation tool of MR image. But some uncertain factors still exist in fuzzy clustering when it is used to segment MR image. These factors, such as the different choice of fuzziness index m, the number of fuzzy clustering c and the distance norm A, affect the speed and precision of fuzzy clustering of MR image tremendously. Specifying the MR image as the object of fuzzy clustering, systematical study and discussion to these uncertain factors, the scheme of parameters choice of fuzzy segmentation is given by this paper.
- 【文献出处】 中国医学物理学杂志 ,Chinese Journal of Medical Physics , 编辑部邮箱 ,2004年02期
- 【分类号】R-39
- 【被引频次】23
- 【下载频次】207