Brain Tumor Detection using Convolution Neural Network with Data Augmentation

Abstract

Detection of brain tumors plays a vital role in medical image processing. If the brain tumors are detected in advance then there is a chance to improve the treatment options and boost the patient’s survival percentage. Brain tumor detection to identify cancer from a significant number of MRI images acquired in medical practice remains as a tedious and complicated task. As a result, there is a need to authomate the image processing based brain tumor detection process. This paper aims to propose an early brain tumor detection method by using a Convolutional Neural Network (CNN) architecture. The positive outcome illustrates the algorithm’s capacity to correctly classify brain tumor images. Performance metrics such as accuracy and F1 score are used to assess the performance of the proposed approach. When compared to conventional methods, the proposed method works efficiently.