AN INVESTIGATION INTO ELECTROMAGNETIC BASED IMPEDANCE TOMOGRAPHY USING REALISTIC HUMAN HEAD MODEL
Journal Title: International Journal of Pharmacy and Pharmaceutical Sciences - Year 2016, Vol 8, Issue 2
Abstract
The objective of this research is to investigate the feasibility of Electromagnetic based Impedance Tomography (EMIT) for brain stroke detection, localization and classification. Electromagnetic based Impedance Tomography employing microwave imaging technique is an emerging brain stroke diagnostic modality. It relies on the significant contrast between dielectric properties of the normal and abnormal brain tissues. To study the interaction between micro-wave signals and head tissues, the simulations are performed using a geometrically simple 3-D ellipsoid head model with emulated stroke. Finite Element numerical technique is adopted to find the solution of Maxwell’s equations to measure the transmitted and backscattered signals in forward problem. Contrast Source Inversion technique is proposed to solve the inverse scattering problem and reconstruct brain images based on calculated dielectric profiles. Detailed analysis is performed to determine the safety limits of transmitted signals to minimize ionizing effects while ensuring maximum penetration. The simulations verify the inhomogeneous and frequency-dispersive behavior of brain tissue’s dielectric properties. The solution of the forward problem demonstrates the microwave signals scattering by the multilayer structure of the head model, duly validated by analytical results. The scattering phenomena can be fully capitalized by image reconstruction algorithm to obtain brain images and detect stroke presence. The initial results obtained in this research and prior work indicates that EMIT-based head imaging system has a potential for rapid stroke detection, classification, and continuous brain monitoring and offers a comparatively cost-effective solution.
Authors and Affiliations
Awais Munawar, Zartasha Mustansar, Ahmed E Nadeem, Mahmood Akhtar
Keywords
Related Articles
- EP ID EP575980
- DOI 10.22159/ijpps.2016v8s2.15217
- Views 60
- Downloads 0
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