Artificial Intelligence Technologies In Magnetic Resonance Imaging: A New Paradigm In Increasing Diagnostic Accuracy And Clinical Decision-Making

Abstract

This article systematically analyzes the application of artificial intelligence (AI) and deep learning algorithms in magnetic resonance imaging (MRI) systems, their role in improving diagnostic accuracy, and their impact on the clinical decision-making process. The study evaluates the clinical effectiveness of AI-based automatic segmentation, pathology classification, and disease outcome prediction models. Special attention is given to the "black-box" problems of AI models, ensuring data privacy, and the concept of Explainable AI (XAI). Furthermore, the existing challenges and future prospects of implementing these innovative technologies into daily clinical practice are widely discussed.