Brain Tumor Image Analysis Using FCM with Enhanced BFA Algorithm

Abstract

In this particular piece of research, we will be integrating the clustering technique with the segmentation algorithm. The fuzzy c means algorithm was utilized for the clustering, while the bacterial foraging algorithm was employed for the segmentation. An algorithm for optimizing bacterial foraging that takes into account the dynamics of infections as shown in medical imaging. The objective function was optimized by the use of bacterial foraging. Cluster validation indexes were applied in order to get the numerical results and best solution discovered by BF-FCM. This was done so that the validation of the composite algorithm could be examined. The newly developed algorithm BF-FCM was able to segment the images of the brain tumor and locate the various components of the tumor. The findings of the trial indicate that the BF-FCM has superior performance.