Accuracy requirements for an automated deep-learning-based slice prescription for cardiac MRI

Motivation: Automated plane prescription tools can make cardiac MRI more accessible, but their accuracy needs to be validated. Goal(s): We aim to determine the accuracy requirements for an AI-driven automated prescription tool. Approach: To determine the accuracy requirements for an AI-driven automated prescription tool we compare landmarks set by the tools to those set manually by operators with different levels of experience. Results: The prototype can match the average performance of an operator group, outperforming the less experienced individuals. Impact: To be reliable the performance of automated prescription tools needs to be established. Here an AI-driven automated prescription tool for cardiac MRI planes could match the average performance of an operator group, outperforming the less experienced individuals.