State of the Art and Prediction Model for Brain Tumor Detection

Magnetic resonance imaging (MRI), an imaging tool, can provide detailed brain images that are used for tumor diagnosis and analysis. Owing to developments in medical imaging and deep learning technology, computerized health care has undergone rapid growth. For image processing and disease prediction, deep learning creates a whole new world. In diagnosing brain disorders and supplying clinical decision support, deep learning has great supremacy. The principle of deep learning is used to carry out an automatic classification of brain tumors using brain MR images and to calculate their performance. Early brain disease diagnosis plays a crucial role in raising the likelihood of recovery and increasing patients' survival rates. This paper seeks to propose a convolutional neural network (CNN)-based model that classifies and predicts MRI images of the patient's brain to detect a brain tumor. The accuracy of 86.63% is obtained in the proposed system.