Passive shimming of a superconducting magnet using the L1-norm regularized least square algorithm

Kong, Xia, Zhu, Minhua, Xia, Ling, Wang, Qiuliang, Li, Yi, Zhu, Xuchen, Liu, Feng and Crozier, Stuart (2016) Passive shimming of a superconducting magnet using the L1-norm regularized least square algorithm. Journal of Magnetic Resonance, 263 122-125. doi:10.1016/j.jmr.2015.11.019


Author Kong, Xia
Zhu, Minhua
Xia, Ling
Wang, Qiuliang
Li, Yi
Zhu, Xuchen
Liu, Feng
Crozier, Stuart
Title Passive shimming of a superconducting magnet using the L1-norm regularized least square algorithm
Formatted title
Passive shimming of a superconducting magnet using the L1-norm regularized least square algorithm
Journal name Journal of Magnetic Resonance   Check publisher's open access policy
ISSN 1096-0856
1090-7807
Publication date 2016-02
Sub-type Article (original research)
DOI 10.1016/j.jmr.2015.11.019
Volume 263
Start page 122
End page 125
Total pages 4
Place of publication Maryland Heights, United States
Publisher Academic Press
Collection year 2017
Language eng
Formatted abstract
The uniformity of the static magnetic field B0 is of prime importance for an MRI system. The passive shimming technique is usually applied to improve the uniformity of the static field by optimizing the layout of a series of steel shims. The steel pieces are fixed in the drawers in the inner bore of the superconducting magnet, and produce a magnetizing field in the imaging region to compensate for the inhomogeneity of the B0 field. In practice, the total mass of steel used for shimming should be minimized, in addition to the field uniformity requirement. This is because the presence of steel shims may introduce a thermal stability problem. The passive shimming procedure is typically realized using the linear programming (LP) method. The LP approach however, is generally slow and also has difficulty balancing the field quality and the total amount of steel for shimming. In this paper, we have developed a new algorithm that is better able to balance the dual constraints of field uniformity and the total mass of the shims. The least square method is used to minimize the magnetic field inhomogeneity over the imaging surface with the total mass of steel being controlled by an L1-norm based constraint. The proposed algorithm has been tested with practical field data, and the results show that, with similar computational cost and mass of shim material, the new algorithm achieves superior field uniformity (43% better for the test case) compared with the conventional linear programming approach.
Keyword L1-norm regularized least square
MRI (Magnetic Resonance Imaging)
Passive shimming
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Information Technology and Electrical Engineering Publications
 
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