Brain Tumor Segmentation based on Outcross Clustering Technique

-Medical imaging is a process of creating visual representation of the interior of a body for clinical analysis and medical intervention, MRI (Magnetic Resonance Imaging) is a powerful anticipate tool that permits to achieve images of internal anatomy of human-body in a sheltered and non-invasive manner, Brain Tumor is the uncontrolled growth of tissue in any part of the brain which is harmful to human of the complexity involved in brain tumor images. Brain tumor extraction and its analysis is the challenging task in the medical image processing. This paper states image segmentation using efficient K-Means, Fuzzy c-means (outcross clustering) with thresholding and level set methods, The algorithm is designed in such a way that it gives exact tumor segmented images with accuracy and reducing of time for analysis, The stage of the tumor is displayed based on the amount of area calculated from the cluster, The performance evaluation is done on the basis of error percentage compared