Tumor Is An Uncontrolled Growth Of Tissue In Any Part Of The Body. The Tumor Is Of Different Types And Has Different Characteristics And Corresponding Different Treatment. If We Find The Tumor In Early Stages, We Can Stop Further Growth Of The Tumor And Proper Treatment Is Undergone For The Tumor. Magnetic Resonance Imaging (MRI) Is The Most Important Techniqu1e, In Discovering The Brain Tumor. This MRI Image Is Visually Examined By The Physician For Detection & Diagnosis Of Brain Tumor. However This Method Of Detection Resists The Accurate Determination Of Stage & Size Of Tumor. To Avoid That, This System Uses Computer Aided Method For Segmentation. There Are Different Types Of Algorithm Were Developed For This Segmentation Purpose But They Have Some Drawback In Detection And Extraction. The Objective Of This Paper Is To Develop An Enhanced K-means And Kernelized Fuzzy C-means For A Segmentation Of Brain Magnetic Resonance Images.
