A Hybrid Approach for Detection and Classification of Brain Tumor

Among many diseases in medical science one of the severe problems, the World isfacing today is brain tumor. Brain tumor is an uncontrollable growth of cell which multiplieswith in the brain. The most well-known imaging technique among available medical imagingtechniques is Magnetic Resonance Imaging (MRI) used to detect presence of tumor in thebrain. Due to huge volumes of medical images are produced at medical centres. Study of thishuge data is done manually and experts find difficult for analysing small size data which isbelow 3 mm size. Hence to analyse brain tumor more accurately image segmentationtechniques plays a vital role and used widely in medical image analysis. Image segmentationis one of the methods that partitions the image into different regions based on somepre-defined criteria. Medical image segmentation is used to separate tumor tissues fromnormal tissues, especially for brain tumors. This helps the clinical expert's quantitativeanalysis, accurate disease diagnosis, detection, classification of brain tumor for malignancyand surgical planning. From literature survey it is noted that, many segmentation techniquesexist to segment brain tumor from MRI mage.