Exploring Image Segmentation Techniques to Examine Abnormalities in Brain Images

Abstract

Early brain tumors are a very difficult task for doctors. MRI images are sensitive to noise and other environmental effects. Therefore, since it is difficult for doctors to detect tumors and their causes, we recommend this procedure to detect brain tumors on images. Here we convert the image to grayscale. We use filters for images to remove noise and other environmental effects from the images. The user needs to select the MRI image of the brain. The system will process the image using the image as a step. We use a unique algorithm to detect tumors from brain images. However, the limits of early imaging of brain tumors are not clear. Therefore, we use image segmentation for the image to find the edges of the image. In this method, we use image segmentation to detect tumors. Here we propose an image segmentation process and a set of image filtering techniques to ensure accuracy. This method was implemented in MATLAB.