Abstract— Brain tumors pose a significant health risk, necessitating early detection and precise analysis to enhance treatment outcomes. Magnetic Resonance Imaging (MRI) is a widely used diagnostic tool due to its non-invasive nature and superior ability to differentiate soft tissue structures. However, the manual interpretation of MRI scans is time-consuming and susceptible to human error, which can lead to misdiagnosis or delayed treatment.
This study proposes a system that integrates MRI with Explainable Artificial Intelligence (XAI) techniques to facilitate early detection and analysis of brain tumors. The primary objectives of this system are to enhance diagnostic accuracy, reduce radiologists’ workload, and provide transparent decision-making insights. By leveraging AI-driven methodologies, this approach aims to improve the efficiency and reliability of tumor identification while offering interpretable explanations to support clinical decision-making.
Keyword: Brain Tumour Analysis, MRI Images, Early Detection, Machine Learning, Deep Learning, Convolutional Neural Networks (CNN), Explainable Artificial Intelligence (XAI).