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.
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.
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.
A new approach to recognizing the shape of the object under study is considered to improve the accuracy of visualiza-tion of electrical impedance tomography data, based on the use of the principal component method, which allows di-viding a new orthogonal space into regions corresponding to the shape of the object under study. The conducted ex-perimental studies have shown the applicability of the proposed approach. The results of studies carried out using bending sensors will improve the design of the electrode belt and improve the quality of visualization of the electrical impedance tomography method.
The article considers a current source for the electrical impedance tomography with compensation in output resistance drop, its block diagram being shown, and its hardware implementation being described. It also presents a technique for assessing the stability of the current source output parameters, a comparison of current sources with and without compensation for the drop in output resistance and amplitude, respectively, has been carried out. It is con-cluded that for a given amplitude of the output current in a given range of frequencies and resistances, a current source with an output resistance drop compensation circuit has an error an order of magnitude smaller than a traditional current source with the same circuitry, and this will positively affect the metrological characteristics of the en-tire electrical impedance tomography device.
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