Researchers have observed that multistage clustering can accelerate convergence and improve clustering quality. Two-stage and two-phase fuzzy C-means (FCM) algorithms have been reported. In this paper, we demonstrate that the FCM clustering algorithm can be improved by the use of static and dynamic single-pass incremental FCM procedures. Keywords-Clustering; Fuzzy C-Means Clustering; Incrementa...

The purpose of this study is to apply fuzzy theory on health care. To achieve this goal, Beck Depression Inventory (BDI)-II was adopted as the instrument and outpatients of a psychiatric clinic were recruited as samples and undergraduates as non-clinical sample as well. To elicit the membership degree, we asked the subjects are free to choose more than one alternative for each item listed in BD...

Glioblastoma multiforme; Necrotic focus; Vasogenic edema; Bilateral filter; Contrast limited adaptive histogram equilization Abstract This paper does the qualitative comparison of Fuzzy C-means (FCM) and k-Means segmentation, with histogram guided initialization, on tumor edema complex MR images. The accuracy of any segmentation scheme depends on its ability to distinguish different tissue clas...

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...

This paper presents a comparison of the three fuzzy based image segmentation methods namely Fuzzy C-Means (FCM), TYPE-II Fuzzy C-Means (T2FCM), and Intuitionistic Fuzzy C-Means (IFCM) for digital images with varied levels of noise. Apart from qualitative performance, the paper also presents quantitative analysis of these three algorithms using four validity functions-Partition coefficient (Vpc)...

Keywords: Cluster analysis Fuzzy clustering Fuzzy c-means (FCM) Initialization Bias correction Probability weight a b s t r a c t Fuzzy clustering is generally an extension of hard clustering and it is based on fuzzy membership partitions. In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the most commonly used clustering method. Numerous studies have presented various generalizations o...