Use of neural networks to improve quality control of interpretations in myocardial perfusion imaging
Background: The aim of this study was to explore the feasibility of using a technique based on artificial neural networks for quality assurance of image reporting. The networks were used to identify potentially suboptimal or erroneous interpretations of myocardial perfusion scintigrams (MPS). Methods: Reversible perfusion defects (ischaemia) in each of five myocardial regions, as interpreted by on
