In medical imaging uncertainty is widely present in data, because of the noise in acquisition and of the partial volume effects originating from the low resolution of sensors. In particular, borders between tissues are not exactly defined and memberships in the boundary regions are intrinsically fuzzy. Therefore, computer assisted unsupervised fuzzy clustering methods turn out to be particularl...

Fuzzy c-means (FCM) clustering is based on minimizing the fuzzy within cluster scatter matrix trace but FCM neglects the between cluster scatter matrix trace that controls the distances between the class centroids. Based on the principle of cluster centers separation, fuzzy cluster centers separation (FCCS) clustering is an extended fuzzy c-means (FCM) clustering algorithm. FCCS attaches import...

By using parameterized representation of fuzzy numbers, criteria for a lower semicontinuous fuzzy mapping defined on a non-empty convex subset of Rn to be a convex fuzzy mapping are obtained. c © 2007 Elsevier Ltd. All rights reserved.

A review of some popular fuzzy cluster validity indices is given. An index that is based on the generalization of silhouettes to fuzzy partitions is compared with the reviewed indices in conjunction with fuzzy c-means clustering.

This article introduces the fuzzy theory. At first, the definition of fuzzy set characterized by membership function is described. Next, definitions of empty fuzzy set and universal fuzzy set and basic operations of these fuzzy sets are shown. At last, exclusive sum and absolute difference which are special operation are introduced. [6] provide the notation and terminology for this paper. In th...

In these notes we review Klimč́ık’s construction of noncommutative gauge theory on the fuzzy supersphere. This theory has an exact SUSY gauge symmetry with a finite number of degrees of freedom and thus in principle it is amenable to the methods of matrix models and Monte Carlo numerical simulations. We also write down in this article a novel fuzzy supersymmetric scalar action on the fuzzy super...

Problem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in ...

Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...