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Abstract #0528

Non-idealized system (NIS) optimization of EPI sequences at ultra-high field.

Daniel West1, Felix Glang2, Jonathan Endres3, David Leitão1, Sarah McElroy4, Moritz Zaiss2,3,5, Jo Hajnal1,6, and Shaihan Malik1,6
1Biomedical Engineering Department, King's College London, London, United Kingdom, 2Max Planck Institute for Biological Cybernetics, University of Tübingen, Tübingen, Germany, 3Institute of Neuroradiology, Universitätsklinik Erlangen, Erlangen, Germany, 4MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, 5Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, 6Centre for the Developing Brain, King's College London, London, United Kingdom

Synopsis

Keywords: System Imperfections, Pulse Sequence Design

Motivation: MRI scanners are built under the assumption of near perfect responses of each subsystem. Computing advances mean that this may no longer be necessary, enabling exploration of cheaper, efficient alternatives.

Goal(s): To allow high-performance scanning with less emphasis on hardware performance, reducing costs and improving access.

Approach: We consider non-idealized system optimization where hardware imperfections are built into a forward model used to optimize pulse sequences via the MR-zero framework. We experimentally demonstrate NIS using measured GIRFs from a 7T system to optimize EPI sequences.

Results: NIS optimization produces sequences that substantially reduce image artefacts even for scenarios that previously exceeded hardware constraints.

Impact: NIS optimization embraces gradient system imperfections, discovering novel acquisition strategies to inherently mitigate them. Although demonstrated on a state-of-the-art 7T scanner, the concept of including imperfections directly into sequence design offers a means to maximize performance of any scanner hardware.

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