Keywords: Breast, Breast, Artificial Intelligence Contrast-enhanced breast MRI exams typically last more than 20 minutes even though the dynamic contrast-enhanced sequences alone would be sufficient for interpretation in over 95% of cases. Thus, we present a personalized on-the-fly MRI protocoling paradigm, where a deep learning algorithm uses images acquired during the first few minutes of the exam to triage patients to an abbreviated versus full MRI protocol. We conduct a retrospective reader study to show that this personalized scanning paradigm decreases scan time and cost while maintaining diagnostic performance.
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