Abstract: In this paper, an attempt has been made to summarize segmentation techniques which are useful for separation of tumor region from brain tumor MRI images. By selecting a proper segmentation technique, it is possible to segment tumor region accurately, which helps in measuring the area of tumor region from brain tumor MRI image. This is possible by using digital image processing tool. Digital image processing is useful for CT scan, MRI, and Ultrasound type of medical images. Digital image processing improves the quality of these medical images using various enhancement techniques. From this enhanced image the radiologist can easily identify infected region and its location. Digital image processing also able to separate out infected region from MRI or CT scan images easily which helps radiologist for diagnoses of the disease at earlier stage. It has several advantages overother imaging techniques, providing high contrast between soft tissues. However, the amount of data isfar too much for manual analysis, which has been one of the biggest obstacles in the effective use of MRI.The detection of tumour requires several processes on MRI images which includes image preprocessing,feature extraction, image enhancement and classification. The final classification process concludes that aperson is diseased or not. Although numerous efforts and promising results are obtained in medicalimaging area, reproducible segmentation and classification of abnormalities are still a challenging taskbecause of the different shapes, locations and image intensities of different types of tumours. In thispaper, various approaches of MRI brain image segmentation algorithms are reviewed and theiradvantages, disadvantages are discussed.
Keywords: MRI, segmentation, morphology, MATLAB.