Abstract
The generalized vector sampled pattern matching (GVSPM) algorithm is widely utilized in the EIT (electrical impedance tomography) reconstruction to solve the ill-posed inverse problem. An improved algorithm, which is called the generalized vector sampled pattern matching-fast (GVSPM-F), is proposed to improve the spatial resolution and reduce the iteration time based on the conventional GVSPM. The GVSPM merely applied the orthogonal projections to approximate the weights in the coordinate directions. The iteration of the proposed GVSPM-F algorithm is calculated in the projection direction of the space constructed by nonlinear correlated column vectors in the column space of the original sensitive matrix. Hence, the proposed GVSPM-F algorithm could achieve stable convergence without an empirical value to preserve the shape information and reduce the time consumption of GVSPM. In the experimental results, GVSPM-F is compared with the traditional GVSPM method in terms of voltage error, iteration time, and image error. The voltage error decreases by approximately 35%, and the number of iteration decreases from thousands to fewer than 100. The image error of GVSPM-F is 6% less than that of GVSPM. The proposed GVSPM-F algorithm is confirmed to be effective for the reconstruction of EIT images.
Highlights
Electric impedance tomography (EIT) is reconstructing the conductivity distribution by the measured surface electrical potential distribution around the target when injecting a current into the object
The purpose of this study is to present a novel generalized vector sampled pattern matching (GVSPM)-F algorithm method to achieve better spatial resolution and location accuracy
In the simulation data, there are four types of prototypes: first, a NaCl solution with a conductivity of 0.8 S/m was added to the circular area with a diameter of 90 mm, and the disturbance with a diameter of 20 mm was added to the centre; second, a 20-mm disturbance is placed in the lower-left portion of a 90-mm-diameter circle filled with NaCl solution; third, a 20-mm-diameter disturbance was placed in the middle, and two 10-mm-diameter disturbances were placed on each side of the 45-degree inclination; fourth, three circular disturbances with diameters of 20 mm were placed at three locations in a triangular shape
Summary
Electric impedance tomography (EIT) is reconstructing the conductivity distribution by the measured surface electrical potential distribution around the target when injecting a current into the object. The surface electrical potential distribution generated by the injected current could be obtained as a solution of Laplace equation, which leads EIT to a functional tomography depending on the medium parameter and boundary condition. It is necessary to solve an inverse parameter problem to realize EIT, which is difficult due to the ill-posed inverse problem. The inverse model is utilized to reconstruct EIT images, and it is difficult to obtain the exact conductivity distribution for image reconstruction due to the ill-posed inverse problem. If the external boundary voltage conditions have a small change, the ill-posed question may make the internal conductivity data change because the electric field has low energy at the centre. The electric field is insensitive to changes in internal conductivity if the electric field has a large change at the centre, and the boundary voltage condition barely changes
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