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Abstract #0551

Interactive Cardiac Magnetic Resonance Imaging using jointly optimized spiral acquisition and deep artifact suppression network.

Olivier Jaubert1, Javier Montalt-Tordera1, Dan Knight2, Simon Arridge3, Jennifer Steeden1, and Vivek Muthurangu1
1Institute of Cardiovascular Sciences, University College London, London, United Kingdom, 2Department of Cardiology, Royal Free London NHS Foundation Trust, London, United Kingdom, 3Department of Computer Science, University College London, London, United Kingdom

Synopsis

Keywords: Heart, Machine Learning/Artificial Intelligence, Interventional, InteractiveInteractive MR sequences have relatively low spatial and temporal resolution due to the limited acquisition and reconstruction time available. We propose to jointly optimize a variable density spiral acquisition and deep artifact suppression network (via a bandit-based approach) to maximize acquisition and reconstruction efficiency and provide interactive high spatio-temporal resolution images. The proposed approach was characterized in simulations and demonstrated prospectively in-vivo, offering promising performance with improved image quality and good handling of abrupt scan-plane changes.

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Keywords