This paper presents a latest survey of different technologies using fuzzy clustering algorithms. Clustering approach is widely used in biomedical field like image segmentation. A different methods are used for medical image segmentation like Improved Fuzzy C Means(IFCM), Possibilistic C Means(PCM),Fuzzy Possibilistic C Means(FPCM), Modified Fuzzy Possibilistic C Means(MFPCM) and Possibilistic F...

We consider the concept of fuzzy quasi-contractions initiated by '{C}iri'{c} in the setting of fuzzy metric spaces and establish fixed point theorems for quasi-contractive mappings and for fuzzy $mathcal{H}$-contractive mappings on M-complete fuzzy metric spaces in the sense of George and Veeramani.The results are illustrated by a representative example.

In this paper, the fuzzy matrix equation $Awidetilde{X}B=widetilde{C}$ in which $A,B$ are $n times n$crisp matrices respectively and $widetilde{C}$ is an $n times n$ arbitrary LR fuzzy numbers matrix, is investigated. A new numerical procedure for calculating the fuzzy solution is designed and a sufficient condition for the existence of strong fuzzy solution is derived. Some examples are ...

introduction: virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. the segmentation of airways from ct images is a critical step for numerous virtual bronchoscopy applications. materials and methods: to overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy c-mean (fc-fcm), utilized...

this paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (fpso) and fuzzy c-means (fcm) algorithms, to solve the fuzzyclustering problem, especially for large sizes. when the problem becomes large, thefcm algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. the pso algorithm does find ago...