Magnetic resonance imaging (MRI) is an important diagnostic imaging technique for the early detection of brain cancer. Brain cancer is one of the most dangerous diseases occurring commonly among human beings. The chances of survival can be increased if the cancer is detected at its early stage. MRI brain image plays a vital role in assisting radiologists to access patients for diagnosis and treatment. Studying of medical image by the Radiologist is not only a tedious and time consuming process but also accuracy depends upon their experience. So, the use of computer aided systems becomes very necessary to overcome these limitations. Even though several automated methods are available, still segmentation of MRI brain image remains as a challenging problem due to its complexity and there is no standard algorithm that can produce satisfactory results. In this review paper, various current methodologies of brain image segmentation using automated algorithms that are accurate and requires little user interaction are reviewed and their advantages, disadvantages are discussed. This review paper guides in combining two or more methods together to produce accurate results.