2 1/2D finite element method for electrical impedance tomography considering the complete electrode model

Bahrani, Navid

doi:10.22215/etd/2012-06960

Cited by 3 publications

(3 citation statements)

References 41 publications

(56 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Electrical impedance tomography (EIT) is one of the methods of medical imaging of the internal structures of the object under study, the principle of operation of which is based on assessing the change in the field in a given section of the object when a low-amplitude highfrequency current is injected through the object (according to a given algorithm) while simultaneously recording the emerging potential differences. [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Method for calculating the heterogeneity of the linear dimensions of the EIT image

et al. 2023

View full text Add to dashboard Cite

The paper proposes a method for calculating the heterogeneity of the linear dimensions of the EIT image. The essence of the method is to identify the region of inhomogeneity Gn by the method of binarization and segmentation and determine its geometric dimensions. The ROI represents a matrix, each element of which is the color value of a particular pixel p. The reconstructed image is being processed. The binarization algorithm processes and determines each element of the matrix, bringing it to a binary form. Next, a w × h matrix is formed and the image is divided into sets p, where, according to the selection criterion Gn, the segmentation procedure is performed using the two-pass ABC-mask method. At the last stage, the geometric dimensions of the inhomogeneity are determined. The results of the analysis of the reconstructed image are presented, the image of the inhomogeneity Gn filtered as a result of binarization and segmentation operations, as well as its geometric parameters are obtained. The operation of the method on computer models for inhomogeneities has been verified. The proposed method allows you to get a clearer and more accurate visualization of the internal structures of the object under study, reduce measurement errors and incorrect solution of the inverse problem.

show abstract

Section: Introductionmentioning

confidence: 99%

Method for calculating the heterogeneity of the linear dimensions of the EIT image

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Electrical impedance tomography (EIT) is a method for visualizing the internal structures of an object under study, based on assessing the change in the conduction field in the plane of the electrode system when a low-amplitude high-frequency current is injected through the object (according to a given algorithm) while simultaneously recording the emerging potential differences. [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Computer model for acquisition, processing, analysis and visualization of measurement data by electrical impedance tomography

et al. 2023

View full text Add to dashboard Cite

In this article, a computer model for the collection, processing, analysis and visualization of measurement data by the method of electrical impedance tomography has been developed. The essence of the work performed is to build a computer model of the phantom, electrodes, conductive medium and inhomogeneities in the COMSOL Multiphysics environment to study the conductivity of objects in order to reduce the error in determining the size of the inhomogeneity in the reconstructed image. The study is performed by placing an inhomogeneity phantom in the conductive region. Based on the data obtained, a matrix of potential differences is constructed using the “near neighbor” algorithm. On its basis, in the GNU Octave environment, using the EIDORS package, a reconstruction of the conducted studies is obtained. With the help of the developed software that implements the method and algorithm for refining the boundaries, filtered images of reconstructions of the results of the studies are obtained. The use of this algorithm makes it possible to reduce the measurement error by a factor of 1.44.

show abstract

“…Solving the problems of improving the correctness of the results of EIT research [1][2][3][4][5] is one of the main directions of its development. This direction is a wide range of tasks aimed at improving the quality of rendered dynamic images.…”

Section: Introductionmentioning

confidence: 99%

Method for clarifying the boundaries of inhomogeneity on a dynamic image for EIT

et al. 2023

View full text Add to dashboard Cite

This article proposes an algorithmic solution to refine the boundaries of heterogeneity in a dynamic image for EIT. The essence of the method is to calculate the rate of change of the color value of each pixel p(i,j) Gn for a given research area. Next, the received data array is processed and the initial image of the heterogeneity region Gn is scaled. Software has been developed that implements the proposed algorithmic solutions. The method of automatic control of the parameters of the EIT examination is implemented, which consists in the automatic mode of operation without operator intervention from the moment of setting the parameters of the examination to the receipt of the final result. The operation of the method for refining the boundaries of inhomogeneity has been tested on computer models. According to the results of the study, the error in determining γ was reduced by 1.44 times. Thus, it seems possible to reduce it when transmitting and digitizing measurement data.

show abstract

2 1/2D finite element method for electrical impedance tomography considering the complete electrode model

Cited by 3 publications

References 41 publications

Method for calculating the heterogeneity of the linear dimensions of the EIT image

Method for calculating the heterogeneity of the linear dimensions of the EIT image

Computer model for acquisition, processing, analysis and visualization of measurement data by electrical impedance tomography

Method for clarifying the boundaries of inhomogeneity on a dynamic image for EIT

Contact Info

Product

Resources

About