Speaker
Description
Background: Magnetic Induction Tomography (MIT) is an electromagnetic imaging technique that maps a material’s electrical conductivity by inducing eddy currents via a primary oscillating magnetic field. The resulting secondary magnetic fields from the eddy currents are measured for image reconstruction and object characterisation. Performing MIT on low-conductivity samples (e.g. human tissue, saline) is valuable but challenging due to weak secondary fields. Optically pumped magnetometers (OPMs), known for high sensitivity, show promise for such applications. We present progress towards an OPM-MIT system for low-conductivity samples, including image reconstruction algorithm development and simulations of secondary field magnitudes.
Methods: Using a Minimum Norm Estimation (MNE) algorithm, we reconstructed images from numerically simulated (via COMSOL) secondary fields. Samples included a 1-cm copper cube (conductivity = 5.998×107 S/m) and copper ‘letters’. A magnetic dipole forward model estimated the dipole source distribution matching the secondary field maps. We also simulated secondary fields from a 1-cm cube with conductivity of 10 S/m.
Results: Samples were placed on a 5-cm square grid. Secondary fields were measured on a 1-cm resolution grid located 1 cm from the sample, with a forward model based on 1-mm pixels. MNE-derived images correlated well with the ground truth (coefficient ≈ 0.8). Simulations indicated the expected linear relationship between conductivity and secondary field magnitude. A 150 µT primary field induced a 300 fT secondary field at 6 mm from a 10 S/m sample.
Outlook: Results suggest MIT of low conductivity samples to be possible using OPMs. Our simulation-based imaging algorithm will next be validated experimentally using a copper sample and fluxgate magnetometer. We will also use insights to advance the design, development and realisation of an OPM-MIT system.
