Intelligent Brain Tumor Detection System using Deep Learning Technique

Abstract

Brain tumors are dangerous and serious disorders affected by uncontrolled cell growth in the brain. Brain tumors are one of the most challenging diseases to cure among the different ailments encountered in medical study. Tumors are classified as either benign or malignant, with benign tumors being non-cancerous and malignant tumors being cancerous from the MRI (Magnetic Resonance Images). There are several tumor detection techniques available, but more study is needed in this field since numerical analysis, precisedisorder diagnosis, and brain tumor detection are all necessary for scientific confirmation. As a result, good planning can protect a person's life that has a brain tumor. Using the 2D Convolutional Neural Network (CNN) technique, this study proposes Computer-Aided Diagnosis (CAD) a deep learning-based intelligent brain tumor detection framework for categorization of brain MRI images with the dataset from Figshare, It is a combination of 3064 brain MRI images from 233 patients into two categories: benign and malignant. The performance of the proposed framework is calculated and compared with state-of-the-art methods in terms of accuracy, recall, and F1-Score.