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Author(s):

Mohammed Gufran | Mohammed Zubairulla Khan | Mohin R Pinjar | Sona J M
Keywords:

Brain Tumor Detection, MRI Analysis, Deep Learning, AI, Flask, Medical Imaging, Diagnostic Support.
Abstract:
Detecting Brain Tumors Early Is Vital For Giving Patients The Best Chance At Successful Treatment And Recovery. This Project Introduces A User-friendly Web Application Designed To Help With The Early Detection Of Brain Tumors Using MRI Scans And Artificial Intelligence (AI). The System Allows Both Doctors And Patients To Upload Brain MRI Images Taken From Four Common Angles: Top, Bottom, Left, And Right. Once Uploaded, These Images Are Processed By A Secure Backend System Built With The Flask Framework. A Pre-trained Deep Learning Model—specifically, A Convolutional Neural Network (CNN)—analyses The Scans To Look For Signs Of Brain Tumors. After The Analysis, The Application Creates A Simple, Easy-to-understand Report That Includes Patient Details, The AI’s Prediction, And A Confidence Score (set Above 90% For Demonstration). The Platform Is Designed To Be Intuitive, Requiring No Technical Background To Use. While It’s Not Meant To Replace Professional Medical Diagnosis, It Can Serve As A Helpful Early Screening Tool, Particularly In Areas With Limited Access To Healthcare. This Work Demonstrates How AI-powered Tools Can Support Faster, More Accessible Medical Insights And Improve Diagnostic Processes.

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