AN OPTIMIZED CNN-BASED APPROACH FOR ACCURATE BRAIN TUMOR IDENTIFICATION AND CATEGORIZATION USING MRI SCANS

Brain tumors are one of the most critical and life-threatening medical conditions, requiring accurate and timely diagnosis for effective treatment. Recent advancements in artificial intelligence and deep learning, particularly Convolutional Neural Networks (CNNs), have demonstrated significant potential in automating tumor detection processes. This project focuses on the development and implementation of a CNN-based system for brain tumor detection using MRI image data. The model aims to classify MRI scans into tumor and non-tumor categories with high accuracy. This report outlines the entire process, from data preprocessing and model design to evaluation and conclusions.