Fuzzy Clustering Methods for the Segmentation of Multivariate Medical Images
نویسندگان
چکیده
In this article, we present some results on the application of fuzzy methods to the segmentation of multivariate medical images. We report the results obtained by using the Fuzzy C-mean (FCM) algorithm by J. Bezdek and the method by K. Rose, E. Gurewitz and G. Fox (RGF) based on the Maximum Entropy Principle (MEP) that avoids any a priori assumption on the number of classes. In particular we study the effect of using, for each new epoch of the algorithm, a Reduced Data Base (RDB) obtained through an uniform random sampling of the original data base. From our experiments the RGF method shows the best efficiency in term of reliability of the solutions while the FCM results faster for big RDBs.
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تاریخ انتشار 1997