Detection and Classification of Brain Tumor Using Convolutional Neural Network

Abstract

Unnatural and uncontrolled proliferation of brain cells is referred to as a brain tumor. As the skull of human is severe, any unanticipated development may compromise a person’s functionality depending on the portion of the brain involved; additionally, it can impact the other body parts and affect the behavior of people. To detect the brain tumor, different imaging techniques are available. But MRI is one of the widely used technique. MRI is based on magnetic field and radio waves that generates quality images of body organs and tissues. After the detection of brain tumor, it is very important to know its type for the further treatment process. Deep Learning which is a subset of Machine Learning has shown impressive performance, specifically in classification and segmentation issues. The classification of several types of brain tumors using dataset of MR images is proposed using a Deep Learning model built on a Convolutional Neural Network. The suggested network topology performs admirably, with the overall accuracy 97.52%. The outcomes show that the model can be used for multiple classifications of brain tumors.