Abstract: MRI images plays important role in auxiliary radiologists approaches for diagnosis and treatment. It is an inventive classification technique to notice normal and abnormal MRI brain image. Medical image like ECG, MRI and CT-scan images are important way to diagnose disease of human being efficiently. The standard analysis of tumor based on visual check up by radiologist is the conjugative method, which may lead to wrong classification when a large number of MRIs are to be analysed. The prospect of endurance can be expanded if the tumor is observed perfectly at its recent stage. Magnetic resonance imaging (MRI) technique is used for the study of the human brain. Segmentation techniques locate tumor location. In this review, classification techniques based on Support Vector Machines (SVM) are suggested and tested to brain image classification with the help of segmentation. The main objective of this paper is to provide a magnificent result of MRI brain tumor classification using SVM. The different segmentation and classification techniques are described here. An efficient techniques are used for segmentation and classifications.

Keywords: Brain tumor, magnetic resonance imaging, support vector machine, ANN.