Federated Learning-Based ResNet-18 Model for Brain Tumor Classification in MRI Scans

Abstract

This study proposes a federated learning framework for brain tumor classification. The diagnostic AI system operates by using ResNet-18 models for scanning MRI images which subsequently enables glioma and meningioma and pituitary tumor and normal brain category recognition. The system supports three user roles including administrator and patient and doctor and allows functions for image upload and distributed training with diagnosis viewing capabilities and appointment scheduling. The system operates under administrator control for managing core functionalities and establishing training sessions and dealing with feedback data to enhance performance. The safe transfer of Brain MRI scans to medical centres through a system which uses AI recommendations allows for enhanced clinical decision processes. Through this platform physicians achieve better report controls which facilitates diagnostic speed and enables active healthcare delivery to patients. The model achieves 98% accuracy while ensuring data privacy, demonstrating clinical potential.