Analyzing ovarian tumor and cancer cells using image processing algorithms K means & fuzzy C-means

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms

Comparative Analysis of K-Means and Fuzzy C-Means Algorithms

In the arena of software, data mining technology has been considered as useful means for identifying patterns and trends of large volume of data. This approach is basically used to extract the unknown pattern from the large set of data for business as well as real time applications. It is a computational intelligence discipline which has emerged as a valuable tool for data analysis, new knowled...

K-Means Clustering using Fuzzy C-Means Based Image Segmentation for Lung Cancer

Lung lesion segmentation refers to the process of partitioning an image into mutually exclusive regions. This study gives a new approach to K-means clustering technique (K-CT) integrated with Fuzzy C-means algorithm for lung segmentation. In the study, large number of images with various types of segmentation was selected and examined. It is followed by thresholding and level set segmentation s...

segmentation of photospheric solar images by using c-means,k-means, and fcm algorithms

Evaluation of Segmentation in Magnetic Resonance Images Using k-Means and Fuzzy c-Means Clustering Algorithms

The purpose of cluster analysis is to partition a data set into a number of disjoint groups or clusters. Members within a cluster are more similar to each other than to members from different clusters. Applicability of the centroid-based k-means and representative object-based fuzzy c-means algorithms for study of the Magnetic Resonance Images is analysed in the work. The two algorithms are imp...