Segmentation and Analysis of Brain MRI Images

Abstract

Image segmentation plays a vital role in the field of medical imaging as it renders better diagnosis and early detection of diseases. The brain is one of the most important organs in the human body as it is responsible for all the actions and reactions in our body. It is the key factor that distinguishes us from other animals. Therefore, brain imaging is important in medical imaging because it helps the doctors to examine and understand the interior of the brain which is active. Magnetic Resonance Imaging is one of the brain imaging techniques. Brain image segmentation is used for measuring and anticipating brain anatomy so that we can figure out any changes in it. The brain tumor is any abnormal or uncontrolled growth of cells in our brain. This project illustrates the application of fuzzy logic in medical imaging, mainly for image segmentation. This uses FCM clustering for providing effective segmentation of blurred boundary areas of the brain. Thus, it segments any abnormalities in the MRI images. This work also uses morphological operations to detect the presence of any brain tumor. The segmentation and analysis of brain anatomy with the help of brain MRI images is the prime objective of this work.