Résumé:
TThe accurate diagnosis of contemporary diseases heavily relies on the processing of medical images.
This study introduces an interesting approach for automated detection of brain tumors from magnetic
resonance imaging (MRI) using the deep learning model ResNet50. This model, renowned for its ability to
extract complex features from images, is deployed to analyze brain MRI images and accurately identify the
presence of tumors. The data used in this study include MRI images containing tumors. We compared
our approach to other methods using criteria such as precision, recall, and F1 score. The proposed
model, ResNet50, achieved a detection accuracy of 98%, demonstrating its effectiveness in detecting
brain tumors from MRI images. These results highlight the potential of the ResNet50 model to improve
early and accurate detection of brain tumors in images.
