Application of synthetic data in the training of artificial intelligence for automated quality assurance in magnetic resonance imaging.
Journal:
Medical physics
Published Date:
Mar 21, 2023
Abstract
BACKGROUND: Magnetic resonance imaging scanner faults can be missed during routine quality assurance (QA) if they are subtle, intermittent, or the test being performed is insensitive to the type of fault. Coil element malfunction is a common fault within MRI scanners, which may go undetected for quite some time. Consequently, this may lead to poor image quality and the potential for misdiagnoses.