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Multi-Channel, Actively Shielded, Power Efficient MRI Z-Gradient Cylindrical Coil Design Using Target-Field Method

Authors :
Haile Baye Kassahun
Sadeq S Alsharafi
Ahmed M Badawi
Abdel-Monem M El-Sharkawy
Source :
IEEE Access, Vol 10, Pp 103840-103851 (2022)
Publication Year :
2022
Publisher :
IEEE, 2022.

Abstract

Gradient coils are essential for MRI where fast and large electrical current pulses are typically applied to conventional, single-channel gradient coils, particularly for high-performance gradient applications. However, these pulses result in significant power losses and heating of the coil. We investigate the design of power-efficient multi-channel Z-gradient coils operating in the conventional mode comparing them to conventional single-channel coils designed using similar dimensions and alike DC performance characteristics. The power-efficiencies of thirteen different two-channel configurations having various section lengths for two different dimensions are analyzed. The current density of each section is approximated by Fourier series expansion where a linear equation relating the desired target field and current density is formulated and then solved. A stream function is derived from the obtained current density and then used to extract the final winding patterns of each section using a particular track width and a specific number of turns. The design process involves optimizing the current driving each channel, the distribution of coil windings, and the section size. Similarly, the performance of three-channel coils is also investigated. Results show that a power dissipation reduction of 17-28% and ~23% can be achieved using two- and three-channel coils, respectively. Moreover, we showed that multi-channel coils may have a slightly better shielding efficiency compared to conventional coils. A new methodology for designing two- and three-channel coils is presented where an advantage in terms of power efficiency can be gained depending on design parameters, coil’s dimensions, number of turns, and other metrics.

Details

Language :
English
ISSN :
21693536
Volume :
10
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.6ba13dd544e24f3da3e581228a2af227
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2022.3210194