Intelligent Brain Tumor Detection System Based on YOLOv8 Deep Learning Model

Finding the brain tumors clearly in MRI scan images is important so doctors can treat patients on time. This work proposed a machine learning framework that utilizes the YOLOv8 model architecture for automated brain tumor recognition. Our approach is to address the limitation through enhanced detection algorithms that deliver an immediate result after passing the scanned picture via our model. The model was trained and validated on MRI dataset. The YOLOv8 achieved a mean average precision () of 85% + , with consistent precision and recall above 0.85 after 20 epochs. Compared with traditional diagnostic approaches, the proposed method demonstrated faster inference times (< 10 ms per image), higher sensitivity to small tumors, and reduced false positives. We have integrated the approach with Gradilo and built a user-friendly interface where the user can upload an image, and it detects back where the tumor is located.