Abstract: “Now-a-days, almost all biomedical science use magnetic resonance image for diagnosis. Segmentation plays a vital role in such biomedical science.. Hence, there is a need to improved result by proposed method as suggested by authors.. Various approaches have been reported in literature for segmentation of brain, where main objective is separating the pixels associated with different types of tissues like white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). This paper introduces an automatic model based technique for brain tissue segmentation from cerebral magnetic resonance (MR) images by using support vector machine (SVM) based classifier. A new and powerful kind of supervised machine learning with high generalization characteristics, is employedby SVM. Another classifier such as neural network plays an important role in biomedical science for improved result for health care system. This paper will analyseSegmentation algorithm and Proved comparative study.”

Keywords: Magnetic Resonance Images,whitematter,graymatter,cerebrospinal fluid,Support vector machine,Neural network