Smart Health App for Identifying Brain Tumors

Abstract

Brain tumors now have become one of the most frequent diseases in the world, and they may be defined as the uncontrolled growth of abnormal cells in the brain, which makes them difficult to detect when compared to tumors in other parts of the body. Brain tumor identification and classification is the most difficult and time-consuming process in medical picture preparation. Magnetic resonance imaging (MRI) is a medical treatment that is used to visualize the interior structure of the body without doing surgery. With this project, the diagnosis process of brain tumors becomes easier with the help of image processing techniques. The thrust of this project is to provide a possible methodology for identifying those tumors, their size, and their regions from MRI images using merging, region splitting, and growth-based segmentation processes within a short time. This process mainly contains five stages: input MRI images, preprocessing, enhancement of images, image segmentation, feature extraction, and classification of tumors. After the MRI images are collected, median filtering and contrast enhancement are used to identify the brain tumors. This system is implemented as a mobile application.