An image reconstruction algorithm of EIT based on pulmonary prior information

doi:10.1007/s11460-009-0020-3

Front Elect Electr Eng Chin

2009, Vol. 4

Issue (2) : 121-126 https://doi.org/10.1007/s11460-009-0020-3

RESEARCH ARTICLE

An image reconstruction algorithm of EIT based on pulmonary prior information

Huaxiang WANG(

), Li HU, Jing WANG, Lu LI

School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China

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Abstract

Using a CT scan of the pulmonary tissue, a human pulmonary model is established combined with the structure property of the human lung tissue using the software COMSOL. Combined with the conductivity contribution information of the human tissue and organ, an image reconstruction method of electrical impedance tomography based on pulmonary prior information is proposed using the conjugate gradient method. Simulation results show that the uniformity index of sensitivity distribution of the pulmonary model is 15.568, which is significantly reduced compared with 34.218 based on the round field. The proposed algorithm improves the uniformity of the sensing field, the image resolution of the conductivity distribution of pulmonary tissue and the quality of the reconstruction image based on pulmonary prior information.

Keywords electrical impedance tomography (EIT) prior information pulmonary model of human image reconstruction COMSOL

Corresponding Author(s): WANG Huaxiang,Email:hxwang@tju.edu.cn

Issue Date: 05 June 2009

Cite this article:

Jing WANG,Huaxiang WANG,Li HU, et al. An image reconstruction algorithm of EIT based on pulmonary prior information[J]. Front Elect Electr Eng Chin, 2009, 4(2): 121-126.

URL:

https://academic.hep.com.cn/fee/EN/10.1007/s11460-009-0020-3
https://academic.hep.com.cn/fee/EN/Y2009/V4/I2/121

Fig.1 Model of round field

Fig.2 CT scan picture

Fig.3 Simulating pulmonary model

Tab.1 Conductivity of biological tissues and organs

Fig.4 Image of pulmonary model mesh

Fig.5 Image of square mesh

Fig.6 Adjacent excitation model

Fig.7 Image of sensitivity distribution based on pulmonary model

Fig.8 Image of sensitivity distribution based on round field

Fig.9 Simulating reconstruction image

Fig.10 Human lung test of EIT

Fig.11 Reconstruction image based on round field

Fig.12 Reconstruction image based on pulmonary model

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