Application of Empirical Wavelet Transform (EWT) on images to explore Brain Tumor

In this paper, a novel method for brain SPECT image feature extraction based on the Empirical Wavelet Transform (EWT) have been proposed. The method is applied to assist the diagnosis of Brain Tumor by the detecting the tumor present in the abnormal brain image. EWT is used to decompose the image into a number of subband images and Fuzzy C-means (FCM) clustering algorithm is used as an image segmentation technique to achieve higher accuracy. After feature extraction, these features are trained and classified using Support vector machine (SVM) classifier. The performance of the proposed approach is evaluated by comparing it with some existing algorithms in case of accuracy, sensitivity, and specificity.