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JOIG 2023 Vol.11(2): 115-120
doi: 10.18178/joig.11.2.115-120

Rapid Analysis of Thorax Images for the Detection of Viral Infections

Roman Radtke and Alexander Jesser*
ICPS, University of Applied Sciences Heilbronn, Germany; Email: roman.radtke@hs-heilbronn.de (R.R.)
*Correspondence: alexander.jesser@hs-heilbronn.de (A.J.)

Manuscript received April 8, 2022; revised May 7, 2022; accepted August 15, 2022.

Abstract—At the end of December 2019, a person in the Chinse city Wuhan was probably infected for the first time with the novel SARS-CoV-2 virus. In order to be able to react as quickly as possible after infection rapid diagnostic measures are of the utmost importance so that medical treatment can be taken at an early stage. An imageprocessing algorithm is presented using chest X-rays to determine whether a lung infection has a viral or a bacterial cause. In comparison to other more complicated evaluation methods, focus was put on using a simple algorithm by using the Canny algorithm for edge detection of infected areas of the lung tissue instead of complex deep learning processes. Main advantage here is that the method is portable to many different computer systems with little effort and does not need huge computing power. This should contribute to a faster diagnosis of SARS-CoV-2 virus-infection, especially in medically underdeveloped areas.

Keywords—COVID-19, X-Ray system, analysis, SARS-CoV- 2, diagnosis, image processing, Canny-algorithm

Cite: Roman Radtke and Alexander Jesser, "Rapid Analysis of Thorax Images for the Detection of Viral Infections," Journal of Image and Graphics, Vol. 11, No. 2, pp. 115-120, June 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.