Automatic distinction between external artifact signals and magnetic resonance signals while searching for independent components

Motivation: Interfering signals, such as, RF noise or electrical discharges outside the MRI target area cause artifacts that reduce image quality or risk diagnostic errors. Goal(s): To identify and correct artifacts by separating the measured signal into MRI signals from the target volume and components from external sources. Approach: The relationship between signals measured in different receive coils depends on the source location. Independent component analysis is employed to separate these different signal components. Activating coils outside the target area aids assigning detected components to internal or external sources. Results: Artifact signals can be extracted from MRI images for different RF interference patterns. Impact: The proposed approach enables low-effort, continuous image quality assurance as well as automatic correction of specific artifacts. Moreover, the method provides insights into potential hardware or interference issues, thereby helping, to reduce system downtime and improving patient appointment availability.