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In medical image processing, Brain tumor segmentation from MRI scan slice without human intervention has become one of the most challenging area in research. MR image slices usually contain a significant amount of noise caused by operator interactions, environmental or external factors, machines used etc, which in turn may cause serious segmentation inaccuracy. Our main aim is to recognize a tumour and its quantification from a specific MRI scan of a brain image to obtain the best segmentation in minimum time. In this paper, we are trying to develop a robust segmentation technique, by combining two segmentation algorithms, expectation maximization and level set. This algorithm framework composed of three stages. 1. Pre-processing is used for background separation of brain; it can be also called as pre-segmentation method 2. Abnormal regions in brain is detected by using Expectation Maximization …