AN APPROACH FOR BRAIN TUMOR SEGMENTATION AND CLASSIFICATION USING aNN

the brain tumors are the mass of undifferentiated cells which form uncontrolled proliferation of cells in the brain. In this paper, I projected segmentation of brain tumor from Magnetic Resonance Images (MRI) using the Region Growing method to track tumor objects in brain images. The key concept in this technique is to separate the position of tumor objects exactly from other items of MR images. Region Growing is useful and simple method which uses several criteria to measure the characteristics of pixel and its neighborhood and also avoids characteristic segmentation errors. Several other algorithms have been proposed to segment brain tumor. Experiments show that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region. In the proposed method, to find the stages of tumor whether it is in Normal, Abnormal or Critical stage we used the technique Artificial Neural Network by the features of the extracted tumor. In order to classify the stages using ANN, we have to implement two algorithms namely Back propagation and Feed forward methods. Thus the final result is obtained as the stages of brain tumor.