• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.159-164
• /
• 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.

• 대한의용생체공학회:의공학회지
• /
• 제10권2호
• /
• pp.102-105
• /
• 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.

• 제어로봇시스템학회논문지
• /
• 제9권1호
• /
• pp.50-56
• /
• 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 new combined method based on genetic algorithm(GA) and modified Newton-Raphson(mNR) algorithm via two-step approach for the solution of the static EIT inverse problem. In the first step, each mesh is classified into three mesh groups: target, background, and temporary groups. The mNR algorithm can be used to determine the region of group. In the second step, the values of these resistivities are determined using genetic algorithm. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved compared to that of the mNR algorithm at the expense of increased computational burden.

• International Journal of Control, Automation, and Systems
• /
• 제3권2호
• /
• pp.211-216
• /
• 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.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
• /
• pp.513-516
• /
• 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.

• 전자공학회논문지
• /
• 제50권3호
• /
• pp.230-236
• /
• 2013

본 논문은 대표적인 손실 매질인 대지에 위치한 도체의 입력임피던스를 MATLAB을 이용한 자체 프로그램을 활용하여 계산하고, 그 결과를 나타내었다. 도체의 입력임피던스는 안테나 이론의 전자계 모델에서 유도된 포클링턴방정식에 모멘트법이 적용되어 계산되었다. 결과의 정확도를 높이기 위해서 기저함수와 가중함수가 삼각함수인 켈러킨법을 적용하였다. 대지에 위치한 도체의 영상분은 수정된 영상법을 적용하여 고려하였다. 도체의 전류분포에 대한 자체 제작한 프로그램 결과와 NEC 프로그램의 결과를 비교하여 프로그램의 신뢰성을 확인하였다. 대지에 위치한 도체의 길이가 1 m, 2 m인 경우에 도전율에 따른 임피던스를 주파수에 따라 시뮬레이션 하였다. 실제 대지에 설치된 도체의 입력임피던스와 위상을 측정하고 동일한 조건에서의 시뮬레이션 결과와 비교하였다.

• 대한수학회논문집
• /
• 제16권3호
• /
• pp.519-541
• /
• 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.

• 전자공학회논문지
• /
• 제49권9호
• /
• pp.293-299
• /
• 2012

전기 임피던스 단층촬영법은 대상체의 표면에 부착된 전극들을 통해 전류를 주입하고 전압을 측정함으로써, 내부의 도전율 또는 저항률 분포를 추정하고 영상으로 복원하는 비교적 새로운 영상 복원 기법이다. 이 논문에서는 on-line에서 한 번의 연산으로도 표적의 정확한 위치 정보와 복원의 정확도를 향상시킬 수 있는 새로운 역문제 알고리즘을 개발하였다. 그리고 제안한 방법의 복원 성능을 향상시키기 위해 가중 행렬의 고유치로부터 step-length를 계산하였다. 몇 가지 시나리오를 설정하고 모의실험을 통해 제안한 방법의 영상 복원의 성능을 평가하였다.

• 전자공학회논문지
• /
• 제54권4호
• /
• pp.83-90
• /
• 2017

전기 임피던스 단층촬영법은 전극을 통해 주입된 전류와 측정된 전압을 기반으로, 내부 도전율 분포를 복원하는 기술로, 비교적 새로운 비파괴 영상 복원 기법이다. 본 논문에서는 이원 혼합물 유동 응용분야에서 온라인으로 적용시킬 수 있도록, 역문제의 계산시간을 줄일 뿐만 아니라 공간 해상도도 함께 향상시킬 수 있는 역문제 해법인 빠른 반복적 가우스-뉴턴 방법을 제안하였다. 제안한 방법의 영상 복원성능을 평가하기 위해 모의실험을 수행하고 그 결과를 비교분석하였다.

• 대한의용생체공학회:의공학회지
• /
• 제30권6호
• /
• pp.461-468
• /
• 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.