Artificial Intelligence for Neuro MRI Acquisition: A Review
It addresses the problem of optimizing MRI acquisition for clinical neuroimaging, but it is incremental as it synthesizes existing research rather than presenting new findings.
This review examines how artificial intelligence methods are being applied to improve neuro MRI acquisition workflows, including planning and artifact correction, with the potential to enhance efficiency and throughput.
Magnetic resonance imaging (MRI) has significantly benefited from the resurgence of artificial intelligence (AI). By leveraging AI's capabilities in large-scale optimization and pattern recognition, innovative methods are transforming the MRI acquisition workflow, including planning, sequence design, and correction of acquisition artifacts. These emerging algorithms demonstrate substantial potential in enhancing the efficiency and throughput of acquisition steps. This review discusses several pivotal AI-based methods in neuro MRI acquisition, focusing on their technological advances, impact on clinical practice, and potential risks.