Abstract
Brain tumors are among the most dangerous and life-threatening health issues, and early detection is crucial for effective treatment. This project presents an AI-powered desktop application designed to classify brain tumors from MRI images using deep learning techniques. The system leverages convolutional neural network (CNN) models such as VGG, Inception, and a custom CNN, which are pre-trained and integrated into a user-friendly GUI developed using PyQt5. The application allows users to upload MRI scans, preprocesses the images with augmentation techniques to improve model robustness, and then predicts tumor types including Glioma, Meningioma, Pituitary tumor, or absence of tumor. The results are displayed with high accuracy and in real-time. This project bridges the gap between medical imaging and artificial intelligence, demonstrating the practicality and effectiveness of machine learning in medical diagnostics.
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