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Electrical conductivity imaging via contactless measurements
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Date
1999-07-01
Author
Gençer, Nevzat Güneri
TEK, MUSTAFA
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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A new imaging modality is introduced to image electrical conductivity of biological tissues via contactless measurements. This modality uses magnetic excitation to induce currents inside the body and measures the magnetic fields of the induced currents. In this study, the mathematical basis of the methodology is analyzed and numerical models are developed to simulate the imaging system. The induced currents are expressed using the (A) over right arrow-phi formulation of the electric field where (A) over right arrow is the magnetic vector potential and phi is the scalar potential function. It is assumed that (A) over right arrow describes the primary magnetic vector potential that exists in the absence of the body. This assumption considerably simplifies the solution of the secondary magnetic fields caused by induced currents. In order to solve phi for objects of arbitrary conductivity distribution a three-dimensional (3-D) finite-element method (FEM) formulation is employed. A specific 7 x 7-coil system is assumed nearby the upper surface of a 10 x 10 x 5-cm conductive body. A sensitivity matrix, which relates the perturbation in measurements to the conductivity perturbations, is calculated. Singular-value decomposition of the sensitivity matrix shows various characteristics of the imaging system. Images are reconstructed using 500 voxels in the image domain, with truncated pseudoinverse. The noise level is assumed to produce a representative signal-to-noise ratio (SNR) of 80 dB. It is observed that it is possible to identify voxel perturbations (of volume 1 cm(3)) at 2 cm depth. However, resolution gradually decreases for deeper conductivity perturbations.
Subject Keywords
Electrical and Electronic Engineering
,
Radiological and Ultrasound Technology
,
Software
,
Computer Science Applications
URI
https://hdl.handle.net/11511/41749
Journal
IEEE TRANSACTIONS ON MEDICAL IMAGING
DOI
https://doi.org/10.1109/42.790461
Collections
Department of Electrical and Electronics Engineering, Article