<title>Multifrequency electrical impedance tomography: tissue characterization and image quality</title>

Electrical impedance tomography (EIT) is an imaging method of the resistivity distribution within a domain. The images are estimated from a set of electrical potential measurements at the boundary of a domain, which are caused by applying current through electrodes fixed at its boundary. In order to improve the image quality, a rotational electrical impedance tomography (REIT) system is proposed to expand the measurement sites by shifting the electrodes. The hard system of REIT is established in the paper, which is composed of three subsystems, rotary scheme, and switches network and measurement system. By injecting the alternating current into the object, a potential will be established on the boundary electrodes of object. The reconstruct results based on REIT system are improved obviously.

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Effect of the number of electrodes on the reconstructed lung shape in electrical impedance tomography

Current Directions in Biomedical Engineering ◽

10.1515/cdbme-2016-0110 ◽

2016 ◽

Vol 2 (1) ◽

pp. 499-502 ◽

Cited By ~ 3

Author(s):

Benjamin Schullcke ◽

Sabine Krueger-Ziolek ◽

Bo Gong ◽

Knut Moeller

Keyword(s):

Image Quality ◽

Electrical Impedance Tomography ◽

Electrical Impedance ◽

Regional Distribution ◽

Current Injection ◽

The Body ◽

Voltage Measurement ◽

Impedance Tomography ◽

The Impact ◽

Stimulation Pattern

AbstractElectrical impedance tomography (EIT) is used to monitor the regional distribution of ventilation in a transversal plane of the thorax. In this manuscript we evaluate the impact of different quantities of electrodes used for current injection and voltage measurement on the reconstructed shape of the lungs. Results indicate that the shape of reconstructed impedance changes in the body depends on the number of electrodes. In this manuscript, we demonstrate that a higher number of electrodes do not necessarily increase the image quality. For the used stimulation pattern, utilizing neighboring electrodes for current injection and voltage measurement, we conclude that the shape of the lungs is best reconstructed if 16 electrodes are used.

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Simulation of effects of the electrode structure and material in the density measuring system of the peripheral nerve based on micro-electrical impedance tomography

Biomedical Engineering / Biomedizinische Technik ◽

10.1515/bmt-2016-0089 ◽

2018 ◽

Vol 63 (2) ◽

pp. 151-161 ◽

Cited By ~ 2

Author(s):

Saber Behkami ◽

Javad Frounchi ◽

Firouz Ghaderi Pakdel ◽

Thomas Stieglitz

Keyword(s):

Image Quality ◽

Peripheral Nerve ◽

Electrical Impedance Tomography ◽

Electrical Impedance ◽

Density Measurement ◽

Measuring System ◽

Reconstructed Image ◽

Electrode Structure ◽

Impedance Tomography ◽

The Real

AbstractThe electrode structure in micro-electrical impedance tomography (MEIT) highly influences the measurement sensitivity and therefore the reconstructed image quality. Hence, optimizing the electrode structure leads to the improvement of image quality in the reconstruction procedure. Although there have been many investigations on electrical impedance tomography (EIT) electrodes, there is no comprehensive study on their influence on images of the peripheral nerve. In this paper, we present a simulation method to study the effects of the electrode structure in the density measurement system of the peripheral nerve based on MEIT. The influence of the electrode structure such as dimensions, material and the number of electrodes and also the recognition feature of different radii of fascicle and different locations of fascicles has been studied. Data were reconstructed from the real and imaginary parts of complex conductivity data, respectively. It has been shown that the material of the electrodes had no effect on the reconstructed images, while the dimensions of the electrodes significantly affected the image sensitivity and thus the image quality. An increase in the number of electrodes increased the amount of data and information content. However, as the number of electrodes increased due to the given perimeter of the peripheral nerve, the area of the electrodes was reduced. This reduction affects the reconstructed image quality. The real and imaginary parts of the data were separately reconstructed for each case. Although, in real EIT systems, the reconstructed images using the real part of the signal have a better signal-to-noise ratio (SNR), this study proved that for a density measuring system of the peripheral nerve, the reconstructed images using the imaginary part of the signal had better quality. This simulation study proposes the effects of the electrode size and material and obtained spatial resolution that was high enough to reconstruct fascicles in a peripheral nerve.

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Improving Image Quality in Electrical Impedance Tomography (EIT) Using Projection Error Propagation-Based Regularization (PEPR) Technique: A Simulation Study

Journal of Electrical Bioimpedance ◽

10.5617/jeb.158 ◽

2019 ◽

Vol 2 (1) ◽

pp. 2-12 ◽

Cited By ~ 32

Author(s):

Tushar Kanti Bera ◽

Samir Kumar Biswas ◽

K. Rajan ◽

J. Nagaraju

Keyword(s):

Image Quality ◽

Electrical Impedance Tomography ◽

Error Propagation ◽

Electrical Impedance ◽

Measured Data ◽

Response Matrix ◽

Reconstruction Accuracy ◽

Impedance Tomography ◽

Reconstruction Process ◽

Projection Error

Abstract A Projection Error Propagation-based Regularization (PEPR) method is proposed and the reconstructed image quality is improved in Electrical Impedance Tomography (EIT). A projection error is produced due to the misfit of the calculated and measured data in the reconstruction process. The variation of the projection error is integrated with response matrix in each iteration and the reconstruction is carried out in EIDORS. The PEPR method is studied with the simulated boundary data for different inhomogeneity geometries. Simulated results demonstrate that the PEPR technique improves image reconstruction precision in EIDORS and hence it can be successfully implemented to increase the reconstruction accuracy in EIT.

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