Keywords: Heart, Machine Learning/Artificial Intelligence, View PlanningCardiac Magnetic Resonance (CMR) is a powerful technique which can be used to perform a comprehensive cardiac examination. However, its adoption is often limited to specialised centres, in part due to the need for highly trained operators to perform the complex procedures of determining the 4 standard cardiac planes: 2-, 3-, 4-chamber and short axis views. To automate view planning, a deep learning-based tool (DeepCardioPlanner) has been proposed to regress the view defining vectors from a rapidly acquired 3D image. It successfully takes advantage of multi-objective learning to allow accurate, fast and reproducible view prescriptions without any operator input.
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