Abstract
MRI images segmentation is a method of extracting and analysing the various parts of input MRI data. Various approaches have been developed to better the efficiency of these segmentation methods. Proposed method in MRI image segmentation is fast fuzzy C-means based class 3 thresholding method. This method uses normally distributed pseudorandom numbers for initial fuzzy estimates. It converges faster than standard method. For improve the segmentation we use CLAHE contrast enhancement method before image segmentation. Method also uses the segmentation results of C mean fuzzy class 3 thresholding as the matching matrices for colour image segmentation. Fuzzy clustering is also evaluated for different exponent value of the partition matrix for better segmentation performance. Results of the proposed segmentation method are tested. It opens the variety of MRI images and performance is evaluated for higher entropy.
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