Early Detection of Brain Tumor from The MRI scan Using Deep Learning

Brain tumors are life-threatening, and early detection is crucial for improving patient outcomes. This research compares three advanced deep learning models—MobileNet, ResNet50V2, and Xception—for detecting brain tumors from MRI scans. The process includes data preprocessing, feature extraction, and binary classification. MobileNet offers computational efficiency, Xception excels in feature extraction, and ResNet50V2 achieves the highest accuracy at over 97%. Performance is evaluated using five-fold cross-validation and metrics such as accuracy, precision, recall, and F1-score. This study highlights the potential of deep learning in enhancing early brain tumor detection and aiding clinical decision-making.