Blockchain-Integrated Neural Networks for Enhanced MRI-Based Brain Tumor Detection: A Revolutionary Approach

Abstract

The integration of blockchain technology with deep learning models represents a groundbreaking advancement in medical diagnostics, particularly in the realm of brain tumor detection from MRI scans. This paper explores the potential of blockchain-integrated neural networks to enhance the accuracy, security, and reliability of MRI-based brain tumor detection systems. By utilizing blockchain's decentralized ledger to ensure secure and immutable storage of medical data, coupled with the powerful image analysis capabilities of convolutional neural networks (CNNs), this approach provides a transformative solution to critical challenges in medical imaging. Drawing on research, particularly the pioneering work of Subrata Banik, Nani Gopal Barai, and FM Shamrat (2023), this paper delves into the evolution of this innovative technology. It highlights its far-reaching implications for improving diagnostic accuracy, data integrity, and trust in AI-driven healthcare solutions, particularly in the detection of brain tumors.