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In this paper, the PSNR based performances of the various fuzzy based algorithms for medical image segmentation is presented. The evaluation of Fuzzy c-means (FCM) algorithm in terms of peak signal to noise ratio (PSNR) is presented for medical image segmentation. Fuzzy c-means (FCM) algorithm has proved its effectiveness for image segmentation. However, still it lacks in getting robustness to noise and outliers, especially in the absence of prior knowledge of the noise. To overcome this problem, different types of fuzzy algorithms are introduced with and without spatial information for medical image segmentation. The algorithm utilizes the spatial neighborhood membership values in the standard kernels are used in the kernel FCM (KFCM) algorithm and modifies the membership weighting of each cluster. In this paper, the available various fuzzy algorithms are tested on brain MRI which degraded by Gaussian noise. The performance is tested in terms of PSNR for the clustering of images.