Powered Brain Tumor Detection System Using YOLOv8

This work presents an AI-based brain tumor detection system built using the YOLOv8 object detection model integrated with the Roboflow cloud inference platform. The system is capable of automatically identifying and classifying brain tumors from MRI images into four categories: Glioma, Meningioma, Pituitary Tumor, and No Tumor. In addition to classification, it also provides accurate localization of tumor regions using bounding box predictions. The proposed solution combines deep learning-based object detection with a full-stack web application developed using the Flask framework and MongoDB database. This allows secure user login, real-time MRI scan processing, and organized storage of previous scan records for easy access and reference. The results show that the system performs well in terms of accuracy, precision, and recall, making it a useful decision-support tool for medical professionals. YOLOv8 enables fast processing and reliable tumor detection, while the use of cloud-based inference through Roboflow removes the need for high-performance local hardware. Overall, the system offers a fast, efficient, and scalable approach for brain tumor detection, helping reduce diagnostic time and supporting early-stage identification. It improves consistency in results and makes AI-based medical imaging more accessible in practical use.

 [1] F. Pereira, A. Pinto, and D. Silva, “Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images,” IEEE Transactions on Medical Imaging, vol. 35, no. 5, pp. 1240–1251, 2016. [2] N. Abiwinanda et al., “Brain Tumor Classification Using Convolutional Neural Network,” World Congress on Medical Physics and Biomedical Engineering, 2018.  [3] I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning, MIT Press, 2016. Actually, https://www.deeplearningbook.org/ [4] python software foundation. “Python Official Documentation.” https://docs.python.org/3/ [5] Flask Project. “Flask Web Framework Documentation.” Flask https://flask.palletsprojects.com/ [6] MongoDB Inc. “MongoDB Manual-Introduction to MongoDB.” MongoDB https://www.mongodb.com/docs/manual/  [7] Roboflow. “Computer Vision Platform Documentation.” Roboflow https://docs.roboflow.com/  [8] Ultralytics. “YOLOv8 Documentation.” Ultralytics YOLOv8 https://docs.ultralytics.com/ [9] G. Jocher et al., “YOLOv8 Repository,” GitHub. https://github.com/ultralytics/ultralytics [10] TensorFlow Team. “TensorFlow Documentation.” https://www.tensorflow.org/