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Segmentation is a process of partitioning the image into several objects. It plays a vital role in many fields such as satellite, remote sensing, object identification, face tracking and most importantly in medical field. In radiology, magnetic resonance imaging (MRI) is used to investigate the human body processes and functions of organisms. In hospitals, this technique has been using widely for medical diagnosis, to find the disease stage and follow-up without exposure to ionizing radiation.Here in this paper, we proposed a novel MR brain image segmentation method for detecting the tumor and finding the tumor area with improved performance over conventional segmentation techniques such as fuzzy c means (FCM), K-means and even that of manual segmentation in terms of precision time and accuracy. Simulation performance shows that the proposed scheme has performed superior to the existing segmentation methods.

international journal of computer science and information technology/international journal of computer science and information technology  (chennai. print)

Segmentation of Magnetic Resonance Brain Tumor Using Integrated Fuzzy K-Means Clustering