Objective Low-field magnetic resonance imaging is currently developing into a valuable diagnostic tool due to its simplicity of magnet array designs. Particularly, this allows the development of scanners as part of educational workshops, thus ensuring knowledge transfer and empowering local scientists to design tailored solutions for specific local problems. To obtain the maximum performance, the magnet needs to be shimmed requiring an automated system measuring the spatial magnetic field distribution. Methods A self-designed measuring probe based on commercial integrated Hall sensor chips is used and optimized by calibrating it in an easy-to-build calibration system. For positioning of the sensor, a low-cost five-degree-of-freedom robot arm is used and improved by camera-based motion tracking for precise localization of the sensor. Results The system is able to map the field of a <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10334_2025_1239_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="43" /> </InlineMediaObject> <EquationSource Format="TEX">$45\text{mT}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>45</mn> <mtext>mT</mtext> </mrow> </math></EquationSource> </InlineEquation>-Halbach desktop MR magnet, as well as a self-designed x-gradient (used inside the magnet) with an efficiency of <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10334_2025_1239_Article_IEq2.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="77" /> </InlineMediaObject> <EquationSource Format="TEX">$2\text{mT}/\text{m}/\text{A}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>2</mn> <mtext>mT</mtext> <mo stretchy="false">/</mo> <mtext>m</mtext> <mo stretchy="false">/</mo> <mtext>A</mtext> </mrow> </math></EquationSource> </InlineEquation>. The built-up Hall sensor demonstrates a level of precision that is competitive with commercial sensors. The entire positioning system can be freely scaled to accommodate larger designs by adjusting the kinematics. Conclusion The presented system is demonstrated to be comparable to already established measurement systems, while the costs, setup times, and mapping duration are greatly reduced.

Easy scalable, low-cost open-source magnetic field detection system for evaluating low-field MRI magnets using a motion-tracked robot

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2025年4月5日

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Pavel Povolni,
Robin Bendfeld,
Sergej Maltsev,
Judith Samlow,
Felix Glang,
Praveen Iyyappan Valsala,
Dominique Goerner,
Dario Bosch,
Sebastian Mueller,
Florian Birk,
Kai Buckenmaier,
Klaus Scheffler

摘要

Objective

Low-field magnetic resonance imaging is currently developing into a valuable diagnostic tool due to its simplicity of magnet array designs. Particularly, this allows the development of scanners as part of educational workshops, thus ensuring knowledge transfer and empowering local scientists to design tailored solutions for specific local problems. To obtain the maximum performance, the magnet needs to be shimmed requiring an automated system measuring the spatial magnetic field distribution.

Methods

A self-designed measuring probe based on commercial integrated Hall sensor chips is used and optimized by calibrating it in an easy-to-build calibration system. For positioning of the sensor, a low-cost five-degree-of-freedom robot arm is used and improved by camera-based motion tracking for precise localization of the sensor.

Results

The system is able to map the field of a $45\text{mT}$ $45 mT$ -Halbach desktop MR magnet, as well as a self-designed x-gradient (used inside the magnet) with an efficiency of $2\text{mT}/\text{m}/\text{A}$ $2 mT / m / A$ . The built-up Hall sensor demonstrates a level of precision that is competitive with commercial sensors. The entire positioning system can be freely scaled to accommodate larger designs by adjusting the kinematics.

Conclusion

The presented system is demonstrated to be comparable to already established measurement systems, while the costs, setup times, and mapping duration are greatly reduced.