Improvement in EIT image reconstruction using genetic algorithm

Kim, H.-C.; Moon, D.-C.; Kim, M.C.; Kim, S.; Lee, Y.J.

doi:10.1109/acc.2002.1024530

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…4 Nonetheless, ERT system has been employed successfully in several geophysical and diagnostic applications. 5 The ERT is an inverse problem. Major issues are its nonlinear nature and poor sensitivity of the boundary voltages to the resistivity of the flow domain deep inside.…”

Section: Introductionmentioning

confidence: 99%

“…Olmi et al, 4 Kim et al 5 and Kuo-Sheng Cheng et al 6 developed a genetic algorithm for static electrical impedance tomography (EIT) image reconstruction and compared with existing algorithms such as mNR. They concluded that the genetic algorithm has relatively good performance in terms of convergence and residual error compared to the mNR.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Two-Stage Genetic Algorithm for Image Reconstruction of Electrical Resistance Tomography

Asgarifar

Frounchi

Zarifi

et al. 2010

Int. J. Model. Simul. Sci. Comput.

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In this paper, we present a combined GA-ERT method based on two-stage genetic algorithm for image reconstruction in electrical resistance tomography (ERT). Image reconstruction in ERT is an ill-posed inverse problem and we have replaced the reverse solver by a two-stage optimization algorithm. The first stage of GA-ERT is reach to an approximate shape and location of the object. Also in this stage, we proposed a new electrode arrangement for ERT forward solver to reduce the process time of the forward problem. In the second stage, the GA employs result of the first stage as an initial population instead of a random group. Therefore with the local zoom, the GA can be employed to obtain the shape and location of the object more precisely. Experimental results of numerically solved ERT by the GA are also presented and compared to those obtained by other more established inversion methods such as modified Newton-Raphson (mNR) and RES2DINV program which is a standard 2-D resistivity inversion program. Results show that the proposed method can efficiently improve the ill-posed condition of ERT image reconstruction problem and can superiorly enhance the quality of ERT images.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%