• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.102-105
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• 1989

In electrical impedance tomography(EIT), we use boundary current and voltage measurements toprovide the information about the cross-sectional distribution of electrical impedance or resistivity. One of the major problems in EIT has been the inaccessibility of internal voltage or current data in finding the internal impedance values. We propose a new image reconstruction method using internal current density data measured by NMR. We obtained a two-dimensional current density distribution within a phantom by processing the real and imaginary MR images from a 4.77 NMR machine. We implemented a resistivity mage reconstruction algorithm using the finite element method and sensitivity matrix. We presented computer simulation results of the mage reconstruction algorithm and furture direction of the research.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.87-91
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• 2002

본 연구는 탐지 대상물체의 형상인식 이 가능한 비접촉, 원격 탐지장치의 개발에 관한 것이다. 형체인식용 비접촉 시스템은 주로 Magneto-Impedance법과 Magneto-Inductance법이 있 으며, Magneto- Inductance법은 왜곡이 적고, 인체나 탐지대상물체에 손상을 가져오지 않는다. 본 연구에서는 2극으로 디자인 된 Magnetic Tomography System을 이용하여 물체의 위치에 따른 투자율 변화량을 계산 및 실측하였다.

• 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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• 2003.10a
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• pp.396-401
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• 2003

Electrical impedance tomography(EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents and measured voltages on the surface of the object. In this paper, an effective dynamic EIT imaging scheme is presented based on the projection filtering to estimate the unknown resistivity distribution. In particular, pre-integration (pre-grouping) technique is employed to stabilize the inverse algorithm. We carried out computer simulations with synthetic data to illustrate the reconstruction performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.134-137
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• 2003

Newton-Raphson is most used algorithm in EIT(electrical impedance tomography), cross-sectional distribution of resistivity is reconstructed by mean of both generating and sensing electrodes attached onto the surface of the object. EIT has been suffered from the severe ill-posedness which is caused by the inherent low sensitivity of boundary measurements to any changes of internal resistivity values. In this paper, we propose modified cost function and weighting factor that compensate for low sensitivity between boundary measurements and internal resistivity and improve performance of Newton-Raphson for EIT in region of interest.

• 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.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.513-516
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• 2002

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 two intelligent optimization algorithm techniques such as genetic algorithm and simulated annealing for the solution of the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, genetic algorithm, and simulated annealing.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.613-619
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• 2008

A method to produce a desired current pattern in a multiple-source EIT system using voltage sources is presented. Application of current patterns to a body is known to be superior to the application of voltage patterns in terms of high spatial frequency noise suppression, resulting in high accuracy in conductivity and permittivity images. Since current sources are difficult and expensive to build, the use of voltage sources to apply the current pattern is desirable. An iterative algorithm presented in this paper generates the necessary voltage pattern that will produce the desired current pattern. The convergence of the algorithm is shown under the condition that the estimation error of the linear mapping matrix from voltage to current is small. Simulation results are presented to illustrate the convergence of the output current.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.39.1-39
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• 2001

Impedance tomography (EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents through the electrodes and induced voltages on the surface of the object. We describe a dynamic EIT imaging technique for the case where the resistivity distribution inside the object changes rapidly within the time taken to acquire a full set of independent measurement data, In doing so, the inverse problem is treated as the nonlinear state estimation problem and the unknown state (resistivity) is estimated with the aid of extended Kalman filter in a minimum mean square error sense. In particular, additional electrodes are attached to the known internal structure of the object ...

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.66-74
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• 2007

We have developed a multi-channel, multi-frequency EIT system with operating frequency of 10Hz to 500KHz. The number of digital voltmeters using phase-sensitive demodulation can be varied from 8 to 64 and we found that 16 and 32-channels are most practical. This paper describes the design, implementation, and construction of 16 and 32-channel systems. The performance of the system was thoroughly tested and we found that CMRR of the developed voltmeter is about 85dB with $100{\Omega}$ unbalancing series resistor. The SNR is greater than 99.6dB and the output impedance of the constant current source is $1{\Omega}W$ at least for all frequencies. Imaging experiments using a banana with frequency-dependent conductivity and permittivity show that frequency-difference imaging is possible using the developed system. Future works of animal and human experiments are discussed.