• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5595-5597
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• 2015

Electrical impedance tomography (EIT) is a new non-invasive, mobile screening method which does not use ionizing radiation to the human breast. It is based on the theory that cancer cells display altered local dielectric properties, thus demonstrating measurably higher conductivity values. This article reviews the utilisation of EIT in breast cancer detection. It could be used as an adjunct to mammography and ultrasonography for breast cancer screening.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.23-28
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• 2004

In EIT, various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. In this paper, a SPSA approach is proposed for the solution of the EIT image reconstruction. Results of numerical experiments of EIT solved by the SPSA approach are presented and compared to that obtained by the modified Newton-Raphson(mNR) method.

• Communications of the Korean Mathematical Society
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• v.16 no.3
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• pp.519-541
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• 2001

Magnetic Resonance Electrical Impedance Tomography(MREIT) is a new medical imaging technique for the cross-sectional conductivity distribution of a human body using both EIT(Electrical Impedance Tomography) and MRI(Magnetic Resonance Imaging) system. MREIT system was designed to enhance EIT imaging system which has inherent low sensitivity of boundary measurements to any changes of internal tissue conductivity values. MREIT utilizes a recent CDI (Current Density Imaging) technique of measuring the internal current density by means of MRI technique. In this paper, a mathematical modeling for MREIT and image reconstruction method called the alternating J-substitution algorithm are presented. Computer simulations show that the alternating J-substitution algorithm provides accurate high-resolution conductivity images.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1327-1331
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• 2014

Background: Electrical impedance tomography (EIT) is a new non-invasive, mobile screening method which does not use ionizing radiation to the human breast; allows conducting quantitative assessment of the images besides the visual interpretation. The aim of this study was to correlate the quantitative assessment and visual interpretation of breast electrical impedance tomographs and associated factors. Materials and Methods: One hundred and fifty mammography patients above 40 years and undergoing EIT were chosen using convenient sampling. Visual interpretation of the images was carried out by a radiologist with minimum of three years experience using the breast imaging - electrical impedance (BI-EIM) classification for detection of abnormalities. A set of thirty blinded EIT images were reinterpreted to determine the intra-rater reliability using kappa. Quantitative assessment was by comparison of the breast average electric conductivity with the norm and correlations with visual interpretation of the images were determined using Chi-square. One-way ANOVA was used to compare the mean electrical conductivity between groups and t-test was used for comparisons with pre-existing Caucasians statistics. Independent t-tests were applied to compare the mean electrical conductivity of women with factors like exogenous hormone use and family history of breast cancer. Results: The mean electrical conductivity of Malaysian women was significantly lower than that of Caucasians (p<0.05). Quantitative assessment of electrical impedance tomography was significantly related with visual interpretation of images of the breast (p<0.05). Conclusions: Quantitative assessment of electrical impedance tomography images was significantly related with visual interpretation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.2
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• pp.120-127
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• 2003

In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm or genetic algorithm at the expense of increased computational burden.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.211-216
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• 2005

In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically, the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.159-164
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• 2004

In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simultaneous perturbation method as an image reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

• Journal of Industrial Technology
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• v.26 no.B
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• pp.221-226
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• 2006

Electrical impedance tomography (EIT) is a technique for determining the electrical conductivity and permittivity distribution within the interior of a body from measurements made on its surface. One recent application area of the EIT is the detection of breast cancer by imaging the conductivity and permittivity distribution inside the breast. The present "gold standard" for breast cancer detection is X-ray mammography, and it is desirable that EIT and X-ray mammography use the same geometry. This paper presents a forward model of a simplified mammography geometry for EIT imaging. The mammography geometry is modeled as a rectangular box with electrode arrays on the top and bottom planes. A forward model for the electrical impedance imaging problem is derived for a homogeneous conductivity distribution and Validated by experiment using a phantom tank.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.576-579
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• 2008

Electrical impedance(EIT) for the multi-phase flow visualization is an imaging modality in which the resistivity distribution of the unknown object is estimated based on the known sets of injected currents and measured voltages on the surface of the object. In this paper, an EIT reconstruction algorithm based on the extended Kalman filter(EKF) is proposed. The EIT reconstruction problem is formulated as a dynamic model which is composed of the state equation and the observation equation, and the unknown resistivity distribution is estimated recursively with the aid of the EKF. To verify the reconstruction performance of the proposed algorithm, experiments with simulated multi-phase flow are performed.

• KIEE International Transactions on Electrophysics and Applications
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• v.4C no.3
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• pp.123-128
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• 2004

In electrical impedance tomography (EIT), the internal resistivity distribution of the unknown object is computed using the boundary voltage data induced by different current patterns using various reconstruction algorithms. This paper presents a new image reconstruction algorithm based on the genetic algorithm (GA) via a two-step approach for the solution of the EIT inverse problem, in particular for the reconstruction of "static" images. The computer simulation for the 32 channels synthetic data shows that the spatial resolution of reconstructed images in the proposed scheme is improved compared to that of the modified Newton-Raphson algorithm at the expense of an increased computational burden.rden.