Multil-Kernels Integration for FCM Algorithm for Medical Image Segmentation using Histogram Analasis
Nookala Venu, Bhuma Anuradha · Indian Journal of Science and Technology · 2015
This paper suggests a new process for medical image segmentation using the mixing of two different multi-kernels with spatial information in Fuzzy C-Means algorithm. In literature, it has proved that the multi-kernels outperform the single kernels. In this paper, the integration of two hyperbolic tangent kernels and two Gaussian kernels are used in the proposed algorithm for clustering of images. The presentation of the proposed algorithm is tested on Open Access Series of Imaging Studies (OASIS) MRI image data base. Also, the histogram psychiatry of MRI images are take place in this manuscript. The evaluation is tested in terms of Vpc, Vpe and Silhouette Value. The results after examination, the proposed method shows a significant enhancement as compared to other existing methods in terms of Vpc, Vpe and Silhouette Value under different Gaussian noises. Keywords: FCM, Fuzzy, Multi-Gaussian Kernal, Multi-Hyperbolic Tangent Function, Multiple-Kernal, Segmentation