CAD systems for brain MRI analysis employ various AI techniques to assist radiologists in interpreting images and detecting abnormalities. These systems must be trained on large datasets encompassing diverse brain pathologies to ensure accurate detection and classification of different diseases. In this research, the use of YOLOv4 and YOLOv5 architectures for brain tumour detection in MRI images is an interesting application of deep learning technology. The performances metrices such as Precision, Recall, F1 Score and mAP are analysed. The coding for this work was developed using Python, utilizing TensorFlow as the platform. Simulations were carried out on Google Colab.

YOLO Network Glioma Tumor Meningioma Tumor Pituitary Tumor MRI Images