<scp>MR</scp> sequence design to account for nonideal gradient performance
This work demonstrates numerical optimization of gradient waveforms, yielding substantially improved image quality when given a model for system imperfections. Although the method as implemented has limited flexibility, it could enable more efficient hardware use and may prove particularly important for maximizing performance of lower-cost systems.
Authors
- Daniel J. West (ORCID: https://orcid.org/0000-0002-0246-5851)
- Shaihan Malik (ORCID: https://orcid.org/0000-0001-8925-9032)
- Felix Glang (ORCID: https://orcid.org/0000-0003-3506-4947)
- Jonathan Endres (ORCID: https://orcid.org/0009-0005-0908-4153)
- Moritz Zaiß (ORCID: https://orcid.org/0000-0001-9780-3616)
- Joseph V. Hajnal (ORCID: https://orcid.org/0000-0002-2690-5495)
- David Leitão (ORCID: https://orcid.org/0000-0001-5853-8602)
Institutions
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- King's College London (GB)
- Universitätsklinikum Erlangen (DE)
- Max Planck Institute for Biological Cybernetics (DE)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1002/mrm.70093
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Wellcome Trust
- National Institute for Health and Care Research
- Department of Health and Social Care
- King's College London
- Max-Planck-Gesellschaft
- Engineering and Physical Sciences Research Council
- Centre For Medical Engineering, King’s College London