DETECTION AND SEPARATION OF RING-SHAPED CLUSTERS USING FUZZY CLUSTERING

A new fuzzy clustering algorithm, designed to detect and characterize ring-shaped clusters and combinations of ring-shaped and compact spher ical clusters, has been developed. This FKR algorithm includes automat ic search for proper initial conditions in the two cases of concentric and excentric (intersected) combinations of clusters. Validity criter ia based on total fuzzy area and fuzzy density are used to estimate th e optimal number of substructures in the data set. The FKR algorithm h as been tested on a variety of simulated combinations of ring-shaped a nd compact spherical clusters, and its performance proved to be very g ood, both in identifying the input shapes and in recovering the input parameters. Application of the FKR algorithm to an MRI image of the he art's left ventricle was aimed to investigate the possibility of using this algorithm as an aid in image processing.