Efficiency of Fuzzy C Means algorithm for Brain Tumor segmentation in MR Brain Images

Background and Objective: Image processing is a technique or set of operations to get meaningful information from an image for the usefulness and effectiveness of images.Image segmentation is an efficient technique in extracting and separating some of the features in the images.Methods: The main objective of this research work is to find the best fit of FCM algorithm over finding the axial and coronal plane of MRI brain imagesvia its accuracy and computational time.In the preprocessing, brain images of MRI have been converted from the DICOM format into standard image.Preprocessing is carried out by Gaussian filter technique to remove the noises in the images.The Fuzzy C Means (FCM) algorithm is implemented to segment the tumor affected region in the MR images.Results: By comparing the histogram values of the images (before and after segmentation) with the cluster center values by the FCM algorithm, the efficiency and accuracy of the algorithm is evaluated.Conclusion: The best fit of FCM algorithm into the axial and coronal plane is identified based on the computational time in this work.