Brain Tumor Detection from MRI Image using Deep Learning

Abstract

In this project, we propose a deep learning-based approach for the automatic detection of brain tumors from magnetic resonance imaging (MRI) scans. The model utilizes convolutional neural networks (CNNs) to analyze intricate patterns within the images, distinguishing between tumor and non-tumor regions. A diverse dataset, encompassing a range of tumor types and sizes, is employed for robust model training. Through meticulous preprocessing and augmentation, the system enhances its ability to generalize to new and unseen cases. The model is rigorously evaluated using established metrics on a separate test set, demonstrating its efficacy in accurate tumor detection. This research contributes to the advancement of automated medical image analysis, offering a potential tool for timely diagnosis and intervention in neurological healthcare settings.