Optimisation of magnetic field sensing with optically pumped magnetometers for magnetic detection electrical impedance tomography.

IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Kai Mason, Florencia Maurino-Alperovich, Kirill Y Aristovich, David S Holder
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引用次数: 0

Abstract

Objective: 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. The purpose of this work was to optimise the number, orientation and size of optically pumped magnetometers for MDEIT and inform the future development of MDEIT-specific magnetometers.

Approach: Computational modelling was used to perform forward and inverse MDEIT modelling. 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.

Main results: Single-axis measurements normal to the surface provided the best image quality, and image quality increased with an increase in sensor number and size. The optimal sensing arrangement balancing image quality and practical implementation was measurement normal to the surface of the scalp using between 48 and 96 magnetometers with a cubic cell with an 18 mm side length.

Significance: 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 the development of a small array of single-axis, highly sensitive, high-bandwidth OPMs should be prioritised for fast neural MDEIT.

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来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
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