Anisotropic conductivity tensor imaging using magnetic induction tomography

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Computational Electromagnetics

Background:

• Magnetic induction tomography (MIT) reconstructs human body conductivity using non-contact measurements.
• Current MIT studies primarily use isotropic conductivity models.
• The human body exhibits complex anisotropic properties, questioning the clinical applicability of isotropic models.

Purpose of the Study:

• To evaluate the feasibility of imaging anisotropic conductivity perturbations in an isotropic medium.
• To assess the imaging of isotropic perturbations within a partially anisotropic background, relevant for lung imaging.
• To compare anisotropic and isotropic solver performance in conductivity reconstruction.

Main Methods:

• A simulation study was conducted using an anisotropic solver based on singular value decomposition.
• Anisotropic and isotropic solvers were used to generate conductivity tensor images.
• The study investigated two scenarios: anisotropic anomalies in an isotropic medium and isotropic anomalies in an anisotropic background.

Main Results:

• Anisotropic modeling is essential for achieving satisfactory conductivity reconstructions.
• Imaging anisotropic anomalies significantly benefits from anisotropic modeling.
• The study addressed the resolvability of individual conductivity tensor components.

Conclusions:

• Conventional isotropic models are insufficient for accurate clinical magnetic induction tomography.
• Anisotropic modeling is vital for reconstructing the heterogeneous and anisotropic conductivity distributions of the human body.
• Accurate conductivity tensor imaging is critical for advancing MIT applications.