Brain Tumor detection using Artificial Intelligence

Abstract: Brain tumors are one of the most urgent forms of brain disease because they require early detection for effective treatment. The traditional method of diagnosing them is through MRI scans by expert Radiologists and is a time- consuming process. This contribution provides an Artificial Intelligence (AI) supported framework for the automatic detection and classification of brain tumors using Deep Learning. The NeuroScout platform is based on a ResNet based Convolutional Neural Network (CNN) algorithm trained on brain MRI images to classify brain tumors into four categories: Glioma, Meningioma, Pituitary Tumor and No Tumor. The NeuroScout platform contains FastAPI for the backend, Next.js for the frontend, and MongoDB for data storage, which implements a full stack medical web application. Google Gemini AI generates a medical explanation, treatment recommendation and prevention guidelines for brain tumors which have been detected by the NeuroScout Platform. A major advantage of this approach is that the NeuroScout system demonstrates a high degree of classification accuracy and provides a simple, intuitive user interface for patients, doctors and administrators alike. By providing an AI and Deep Learning based medical support system to healthcare professionals for early diagnosis, this approach will help provide greater access to AI based medical decision support systems.

Keywords: Brain Tumor Detection, Deep Learning, MRI Analysis, ResNet, Artificial Intelligence, Medical Image Processing, Machine Learning, Healthcare AI.