• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.461-468
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• 2009

Magnetic resonance electrical impedance tomography (MREIT) enables us to perform high-resolution conductivity imaging of an electrically conducting object. Injecting low-frequency current through a pair of surface electrodes, we measure an induced magnetic flux density using an MRI scanner and this requires a sophisticated MR phase imaging method. Applying a conductivity image reconstruction algorithm to measured magnetic flux density data subject to multiple injection currents, we can produce multi-slice cross-sectional conductivity images. When there exists a local region of fat, the well-known chemical shift phenomenon produces misalignments of pixels in MR images. This may result in artifacts in magnetic flux density image and consequently in conductivity image. In this paper, we investigate chemical shift artifact correction in MREIT based on the well-known three-point Dixon technique. The major difference is in the fact that we must focus on the phase image in MREIT. Using three Dixon data sets, we explain how to calculate a magnetic flux density image without chemical shift artifact. We test the correction method through imaging experiments of a cheese phantom and postmortem canine head. Experimental results clearly show that the method effectively eliminates artifacts related with the chemical shift phenomenon in a reconstructed conductivity image.

• Journal of Biomedical Engineering Research
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• v.22 no.6
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• pp.503-510
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• 2001

In this paper. we describe a 32-channel bioimpedance measurement system It consists of 32 independent constant current sources of 50 kHz sinusoid. The amplitude of each current source can be adjusted using a 12-bit MDAC. After we applied a pattern of injection currents through 32 current injection electrodes. we measured induced boundary voltages using a variable-gain narrow-band instrumentation amplifier. a Phase-sensitive demodulator. and a 12-bit ADC. The system is interfaced to a PC for the control and data acquisition. We used the system to detect anomalies with different resistivity values in a saline Phantom with 290mm diameter The accuracy of the developed system was estimated as 2.42% and we found that anomalies larger than 8mm in diameter can be detected. We Plan to improve the accuracy by using a digital oscillator improved current sources by feedback control, Phase-sensitive A/D conversion. etc. to detect anomalies smaller than 1mm in diameter.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.215-221
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• 2005

We describe the development of a prototype multi-channel electrical impedance tomography (EIT) system. The EIT system can be equipped with either a single-ended current source or a balanced current source. Each current source can inject current between any chosen pair of electrodes. In order to reduce the data acquisition time, we implemented multiple digital voltmeters simultaneously acquiring and demodulating voltage signals. Each voltmeter measures a differential voltage between a fixed pair of adjacent electrodes. All voltmeters are configured in a radially symmetric architecture to optimize the routing of wires and minimize cross-talks. To maximize the signal-to-noise ratio, we implemented techniques such as digital waveform generation, Howland current pump circuit with a generalized impedance converter, digital phase-sensitive demodulation, tri-axial cables with both grounded and driven shields, and others. The performance of the EIT system was evaluated in terms of common-mode rejection ratio, signal-to-noise ratio, and reciprocity error. Future design of a more innovative EIT system including battery operation, miniaturization, and wireless techniques is suggested.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.553-558
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• 2003

The boundary estimation problem is used to estimate the shape of organic depend on the phase of the cardiac cycle or interested in the detection of the location and size of anomalies with resistivity values different from the background tissues such as nuclear reactor. And we can use the method to solve the optimal solution such as modified Newton raphson, kalman filter, extended kalman filter, etc. But, this method consumes much time and is sensitive to the initial value and noise in the estimation of the unknown shape. In the paper, we propose that multi-layer neural networks estimate the boundary of the unknown object using Fourier coefficient. This method can be used at the real time estimation and have strong characteristics at the noise and initial value. It uses voltage change; difference the homogeneous voltage to the non-homogeneous voltage, and change of Fourier coefficient change to train multi-layer neural network. After train, we can have real time estimation using this method.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.261-268
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• 2004

Osteoporosis is a clinical condition in which the amount of bone tissue is reduced and the likelihood of fracture is increased. It is known that the electrical property of the bone is related to its density, and, in particular, the electrical resistance of the bone decreases as the bone loss increases. This implies that the electrical property of bone may be an useful parameter to diagnose osteoporosis, provided that it can be readily measured. The study attempted to evaluate the electrical conductivity of bone using a technique of electrical impedance tomography (EIT). It nay not be easy in general to get an EIT for the bone due to the big difference (an order of 2) of electrical properties between the bone and the surrounding soft tissue. In the present study, we took an adaptive mesh regeneration technique originally developed for the detection of two phase boundaries and modified it to be able to reconstruct the electrical conductivity inside the boundary provided that the geometry of the boundary was given. Numerical simulation was carried out for a tibia phantom, circular cylindrical phantom (radius of 40 mm) inside of which there is an ellipsoidal homeogenous tibia bone (short and long radius are 17 mm and 15 mm, respectively) surrounded by the soft tissue. The bone was located in the 15 mm above from the center of the circular cross section of the phantom. The electrical conductivity of the soft tissue was set to be 4 mS/cm and varies from 0.01 to 1 ms/cm for the bone. The simulation considered measurement errors in order to look into its effects. The simulated results showed that, if the measurement error was maintained less than 5 %, the reconstructed electrical conductivity of the bone was within 10 % errors. The accuracy increased with the electrical conductivity of the bone, as expected. This indicates that the present technique provides more accurate information for osteoporotic bones. It should be noted that tile simulation is based on a simple two phase image for the bone and the surrounding soft tissue when its anatomical information is provided. Nevertheless, the study indicates the possibility that the EIT technique may be used as a new means to detect the bone loss leading to osteoporotic fractures.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.36-39
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• 2004

Electrical impedance tomography (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. So, small noise occur unexpected reconstruction image. Generally in EIT system, if measured voltage includes noise, we can't find object location and resistivity values. In this paper, we propose digital filter for measured voltage in EIT. Newton-Raphson is the most..popular algorithm in EIT, but noise cause to blur image. We use Fourier transform (FT) in order to minimize the noise and design the filter. After filtering, result of reconstruction image is improved better than before filtering.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.45.4-45
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• 2002

In EIT, an array of disjoint electrodes is attached on the boundary of the object and a set of small alternating electrical currents is injected into the object through these electrodes, and then the corresponding set of voltages is measured on the same array of the electrodes. The objective in EIT is to estimate the resistivity distribution inside the object based on the set of measured voltages and injected currents. In this paper, we proposed a new dynamic EIT reconstruction scheme based on the interacting multiple model (IMM) algorithm. The main contribution of the proposed scheme is that multiple models are employed for the state evolution to get around the modeling uncertainty. Extensi...

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.2
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• pp.77-105
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• 2014

Medical imaging techniques have evolved to expand our ability to visualize new contrast information of electrical, optical, and mechanical properties of tissues in the human body using noninvasive measurement methods. In particular, electrical tissue property imaging techniques have received considerable attention for the last few decades since electrical properties of biological tissues and organs change with their physiological functions and pathological states. We can express the electrical tissue properties as the frequency-dependent admittivity, which can be measured in a macroscopic scale by assessing the relation between the time-harmonic electric field and current density. The main issue is to reconstruct spectroscopic admittivity images from 10 Hz to 1 MHz, for example, with reasonably high spatial and temporal resolutions. It requires a solution of a nonlinear inverse problem involving Maxwell's equations. To solve the inverse problem with practical significance, we need deep knowledge on its mathematical formulation of underlying physical phenomena, implementation of image reconstruction algorithms, and practical limitations associated with the measurement sensitivity, specificity, noise, and data acquisition time. This paper discusses a number of issues in electrical tissue property imaging modalities and their future directions.

• Journal of the Korean Solar Energy Society
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• v.21 no.2
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• pp.69-78
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• 2001

This paper introduces the physical phenomena involved in Direct Contact Heat Exchangers (DCHXs) and also investigates the possibility of applying of EIT(Electrical Impedance Tomography) technique for capturing the images of dispersed phases as they stream through a stagnant body of water. A number of cases are studied where two dimensional cross-sectional static images are given for fictitious and actual masses present in a column of water(saline solution). In most direct contact liquid-liquid heat exchangers, oil or hydrocarbon with a density different(lighter or heavier) from water is normally used as dispersed working fluid. The main difficulty that arises with this arrangement lies in the elucidation of complicated flow field where the dispersed phase fluid tends to change its shape and size constantly during its journey through the other phase(water). This paper presents a number of results with different types of dispersed phases that are immiscible with water. The EIT technique has been employed in this context to test its applicability in capturing the dynamic images of dispersed phases. It shows static images of dispersed phases where dynamic images could be obtained by simply extending the algorithms and strategies employed in the present analysis.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.91-99
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• 1996

A hybrid approach employing both the genetic algorithm and the newton-raphson method is proposed for the electrical impedance computed tomography (EICT) image reconstruction. Computational experiments based on the new concept have shown promising results for several noise-free models. In particular, the resistance distribution of the tested models having resistivity ratio up to 100:1 has been reconstructed sucessfully. Using the proposed mehtod, it is also possible to get the reconstruction by the conventional iterative approaches be difficult to vonverge to a robust solution. If the compution power is enhanced further, the proposed method is expected to stimulate the practical applications of the EICT technology in the near future.