1–6 Jul 2025
Omni Boston Hotel at the Seaport
US/Eastern timezone

Thu-Af-Po.04-04: Active shimming method for a 7T MRI superconducting magnet

3 Jul 2025, 14:00
2h
Ensemble Ballroom, Level 2

Ensemble Ballroom, Level 2

Speaker

Haoran Chen (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, People’s Republic of China)

Description

In the design of ultrahigh field magnetic resonance imaging (MRI) superconducting magnets, it typically requires a high homogeneous magnetic field in the diameter of spherical volume (DSV) to obtain high quality image. Spherical harmonic based B0 shimming relies significantly on the fitting process, which can be computationally demanding, especially when handling a large number of shim coils. This study introduces an active shimming method that optimizes magnetic field homogeneity by acquiring the FID signal at each layer. It uses the full width at half maximum (FWHM) of the spectrum for each layer as a metric and iteratively adjusts the shim coil current. By minimizing the FWHM, this approach efficiently identifies the optimal shimming coil current, significantly enhancing spatial field homogeneity. The experimental validation conducted on a 7 T MRI superconducting magnet confirmed the efficacy of the suggested approach. Specifically, employing gradient coils and active shim coils, the active shimming approach increased the field homogeneity of a 130 mm DSV, resulting in a much better magnetic field environment for subsequent MRI. Furthermore, this method enables rapid shimming before imaging, substantially reducing the time required for imaging preparation.

Author

Haoran Chen (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, People’s Republic of China)

Co-authors

Yaohui Wang (Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, People’s Republic of China) Liang Li (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, People’s Republic of China) Dr Feng Liu (School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Brisbane, QLD 4072, Australia) Qiuliang Wang (Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, People’s Republic of China)

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