Objective: The purpose of this study was to evaluate a clustering method that gets the similarity between the classes, where the comparison measure controls how the clusters are formed.
Methods: The clinical ultrasound images of the cervix were obtained by C.S.I. Mission Hospital- International Cancer Center, Neyyoor. The regular ways of arranging the image in the format of bmp and the dimensions of 256× 256.For investigation, different ultrasound cervix images were tested with the maximum iteration.
Results: This provides the information pattern with the missing values so that the clustering results are enhanced.
Conclusion: The kernel based clustering method and the objective function gives healthier information and also greatest outcome for overlapped information set.
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