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Pixel clustering in spectral domain is an important approach for the soft-tissue categorization of magnetic resonance (MR) brain images. In this regard, clustering algorithms based on type-1 fuzzy set theory are suitable for the overlapping partitions while the rough set based clustering algorithms deal with uncertainty and vagueness. However, additional degree of fuzziness makes the clustering more...
Clustering algorithms based on type-I fuzzy set theory have been used for handling overlapping partitioning area over the last few decades. However, these fail to deal with additional degree of fuzziness within the real life datasets, because the membership values of type-I fuzzy set are crisp real numbers. Therefore, since inception, the type-II fuzzy set theory has been studied to address the weakness...
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