Optimisation of Magnetic Field Sensing with Optically Pumped Magnetometers for Magnetic Detection Electrical Impedance Tomography

TL;DR

This study uses computational modeling to optimize the design and configuration of optically pumped magnetometers for improved magnetic detection in electrical impedance tomography, aiming to enable non-invasive brain imaging.

Contribution

It identifies optimal sensor size, number, and orientation for magnetometers tailored to MDEIT, guiding future sensor development.

Findings

Single-axis sensors normal to the surface yield best image quality.

Increasing sensor number and size improves image quality.

Small arrays of single-axis, highly sensitive sensors are optimal.

Abstract

Magnetic Detection Electrical Impedance Tomography is a novel technique that could enable non-invasive imaging of fast neural activity in the brain. However, commercial magnetometers are not suited to its technical requirements. Computational modelling was used to determine the optimal number, size and orientation of magnetometers, to inform the future development of MDEIT-specific magnetometers. Images were reconstructed using three sensing axes, arrays of 16 to 160 magnetometers, and cell sizes ranging from 1 to 18 mm. Image quality was evaluated visually and with the weighted spatial variance. Single-axis measurements normal to the surface provided the best image quality, and image quality increased with an increase in sensor number and size. This study can inform future OPM design, showing the size of the vapour cell need not be constrained to that of commercially available OPMs, and that a small array of single-axis, highly sensitive sensors is optimal for MDEIT.