Optimized Brain Tumor Detection: A Dual-Module Approach for MRI Image Enhancement and Tumor Classification

A brain tumor diagnosis is one of the most difficult challenges a person can face. While MRI scans are incredible tools for seeing inside the brain, reading them takes time and a high level of precision. To help doctors provide faster, more accurate answers, we’ve developed a new automated system. By "cleaning up" digital images to make them clearer and using smart technology to spot abnormalities, our goal is to take the guesswork out of the process. This isn’t just about better data; it’s about giving patients and their families the clarity and quick action they deserve. Doctors rely on MRIs to find brain tumors, but even the best scans can sometimes be grainy or difficult to read. We created a framework that acts like a "high-definition" filter for medical imaging. First, it scrubs away digital noise and balances the lighting, making tumors stand out from healthy tissue. Then, a trained computer model double-checks the image for signs of illness.