Numerical Function Optimization in Brain Tumor Regions Using Reconfigured Multi-Objective Bat Optimization Algorithm

Medical imaging has evolved as an essential component in many avenues of bio-medical research and clinical practices. It is a vast research area that is used to view the interior parts of the body for the diagnosis of diseases. Brain tumor extraction is a very crucial and highly challenging task in the medical field for that the MRI images are considered for the diagnosis of pathological structures present in the brain. Tumor segmentation using MRI image is done manually by the medical practitioners it causes inaccurate results due to the variability of size and shape of the brain tumors. In this paper, we have proposed the Multi-Objective Bat (MOB) Optimization followed by the Fuzzy-C-Means (FCM) Clustering to segment the tumor region efficiently with intelligent Wireless Sensor Network using NEMS for monitoring real world phenomenon. As a result, it provides the better sub-optimal solution compared with the existing approaches.