This project uses deep learning to detect and localize brain tumors from MRI scans. It uses a ResNet50 model for classification and a ResUNet model for segmentation. It evaluates the models on a dataset of LGG brain tumors.

Developed a machine learning solution utilizing VGG-16 architecture for precise identification and localization of brain tumors in MRI images.

CNN-based brain tumor detection and classification from MRI, achieving high accuracy in identification and localization, proving deep learning’s effectiveness in medical imaging.