AN EFFICIENT BRAIN TUMOR DETECTION USING EXPECTATION MAXIMIZATION ALGORITHM

Brain tumor is a deadly disease. The detection of brain tumor from Magnetic Resonance Imaging (MRI) is a challenging one. The accuracy in the detection of tumor growth in different regions of brain depends upon t he selection of various segmentation and feature extraction techniques. Although multimodal MRI images can provide complementary information in the tumor area, brain tumor segmentation is still a challenging and difficult task. Varying intensity of tumors in MRI makes the automatic segmentation of such tumors extremely challenging. In this paper, we propose a novel method for the detection of brain tumor growth. For preprocessing and segmentation of MRI images, K - means clustering and Expectation - Maximizatio n (EM) algorithms are used. The features are extracted and the proposed techniques provide better performance for tumor detection