A Novel Spline Algorithm Applied to COVID-19 Computed Tomography Image Reconstruction

Abstract

In the information age, image processing technologies play a vital role in the field of industrial engineering. In this article, a novel spline scheme called the hierarchical polishing splines algorithm is proposed, and it is applied to the field of computed tomography (CT) image reconstruction of coronavirus disease 2019 (COVID-19). The proposed algorithm defines a set of control lattices, wherein the density of lattice points in these control lattice ranges from coarse to fine in order, and the final applied function is produced by adding the functions derived from every control lattices. In order to demonstrate the performance of the proposed algorithm, some CT images from COVID-19 patients are selected. The experimental results show that the reconstructed COVID-19 CT images by using the proposed algorithm have good quality when compared with some widely used approaches. In addition, this article also applies the proposed algorithm to reconstruct the infected regions derived from COVID-19 CT images, and the results also show that the proposed algorithm is more efficient than others. Besides, the applicability of the proposed algorithm is discussed, wherein the COVID-19 severity is estimated based on the reconstructed COVID-19 CT images, and the applicability analysis shows that the use of the proposed algorithm to reconstruct COVID-19 CT images can help to achieve more accurate severity assessment of COVID-19 in a certain extent.