Finite element modelling and image reconstruction for Lorentz force electrical impedance tomography

Area of Science:

• Biomedical Engineering
• Computational Physics
• Electrical Engineering

Background:

• Lorentz force electrical impedance tomography (LFEIT) is an emerging imaging modality.
• Accurate modeling of electrodes and their contact impedance is critical for LFEIT performance.
• Current LFEIT methods may require extensive electrode configurations, increasing complexity and acquisition time.

Purpose of the Study:

• To develop a numerical framework for simulating LFEIT measurements with accurate electrode models.
• To propose an efficient image reconstruction scheme for LFEIT using limited electrode data.
• To investigate the impact of electrode modeling on LFEIT measurement accuracy and image reconstruction.

Main Methods:

• A finite element-based complete electrode model was developed, incorporating electrode geometry and contact impedance.
• A modified J-substitution algorithm was employed for image reconstruction.
• Simulations were performed using LFEIT and impedance measurements from two pairs of electrodes.

Main Results:

• Electrode modeling significantly influences LFEIT measurements.
• Inaccuracies in electrode models can negatively impact image reconstruction quality.
• The proposed method requires data from only two electrode pairs, simplifying the setup.

Conclusions:

• Accurate electrode modeling is essential for reliable LFEIT.
• The developed framework and reconstruction algorithm enable efficient LFEIT with reduced electrode requirements.
• This approach offers potential for faster, simpler, and more effective LFEIT imaging.