Application of the generalized vector sampled pattern matching method to reconstruction of electrical capacitance CT images

Abstract

A new reconstruction method called generalized vector sampled pattern matching (GVSPM) has been applied to an ill-posed inverse problem involving electrical capacitance computed tomography for solid-air two-phase flow. This new method is able to achieve stable convergence without the use of an empirical value. This accurate reconstruction is accomplished using an objective function that is calculated as the inner product calculation between the experimental capacitance and the reconstructed image capacitance. The GVSPM method is compared with the conventional Landweber (LW) and iterative Tikhonov regularization (ITR) methods in terms of capacitance residual, image error and image correlation. Overall, the accuracy is strongly dependent upon the image type and the iteration number, however the GVSPM method proved superior to the LW and the ITR methods in the case of annular pseudo particle images.

ECT measurement and CFD–DEM simulation of particle distribution in a down-flow fluidized bed

“…The total measurement time is 5 s, and the total number of frames of the reconstructed image N t is 500. The generalized vector sampled pattern matching (GVSPM) method was used for image reconstruction [20]. Table 3 shows the distribution images of particle volume fraction obtained from experiment and simulation.…”

An Improved Algorithm GVSPM-F for Electrical Impedance Tomography

“…The key idea of the GVSPM is that the objective function is the angle obtained from the inner product between the input vector and the solution of a system of equations. GVSPM has been widely utilized to solve the ill-posed inverse problem, and it has many applications such as the images of yeast cell sedimentary distribution in a multilayered microchannel [24], solid-air two-phase flow [25], and 3D images for Perspex [26]. The recently proposed EIT research is used to monitor patients with COVID-19 [27]- [28] and measure the postoperative lung volumes [29].…”

Simulation Studies on Image Reconstruction Algorithm for Portable Electrical Capacitance Tomography

“…Both of these methods depend on empirical values to reconstruct the accurate image. Takei & Saito (2004) [12] introduced generalized vector sampled pattern matching method to overcome the drawbacks of Tikhonov regularization and Landweber iteration.…”