DocumentCode
2206936
Title
Electrical impedance image reconstruction using the genetic algorithm
Author
Cheng, Kuo-Sheng ; Chen, Bae-Horng ; Tong, Han-Seng
Author_Institution
Inst. of Biomed. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Volume
2
fYear
1996
fDate
31 Oct-3 Nov 1996
Firstpage
768
Abstract
In this paper, a genetic based reconstruction algorithm (GA) is proposed for producing the electrical impedance image. This method has the potential in parallelized hardware implementation. The impedance image reconstruction is cast as a minimization problem. The cost function is defined as the errors between the measured and estimated boundary voltages in least square sense. The image is considered as the bit strings. From the results, it is demonstrated to be feasible for producing the dynamic image. In order to reduce the number of degrees of freedom of this proposed method, a guided technique based upon the voltage measurements is also designed. In addition, the noise effect of the voltage measurement is also investigated. From the simulation results, the proposed algorithm has the some extent of the noise immunity
Keywords
electric impedance imaging; genetic algorithms; image reconstruction; inverse problems; medical image processing; mesh generation; minimisation; FEM; bit strings; cost function; dynamic image; electrical impedance image reconstruction; electrical impedance tomography; forward solver; genetic algorithm; global minimum; least square error; minimization problem; noise effect; noise immunity; parallelized hardware implementation; simulation; voltage measurements; Conductivity; Cost function; Equations; Genetic algorithms; Image reconstruction; Impedance; Least squares methods; Minimization methods; Reconstruction algorithms; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Conference_Location
Amsterdam
Print_ISBN
0-7803-3811-1
Type
conf
DOI
10.1109/IEMBS.1996.651967
Filename
651967
Link To Document