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Region of interest-bounded COVID-19 lung screening using images from portable X-ray devices

4 pagesPublished: February 16, 2023

Abstract

X-ray analysis of the lungs was the main method to assess the degree of affliction of SARS-COV-2. Due to the high contagiousness of this pathology, this assessment was conducted using portable X-ray devices. Automatic methodologies were proposed to compensate the image quality of said portable X-ray devices. However, these methodologies were shown to be exploiting external information (such as pacemakers or ventilators present in the images) to determine the severity. For this reason, we present a methodology specially designed to reduce the effect on an automatic methodology of these extraneous artifacts. We extract the lung region and we perform a screening of the presence of the pathology using only the pulmonary region. Finally, to ascertain the performance of the system (and provide explainability to the clinical experts), we generate the corresponding activation maps. The presented methodology has achieved a more than satisfactory performance in all the scenarios and the activation maps clearly indicate that the system is successfully using information from the lung region while excluding elements unrelated to the disease.

Keyphrases: CAD system, COVID-19, Lung segmentation, radiography, Screening, X-ray

In: Alvaro Leitao and Lucía Ramos (editors). Proceedings of V XoveTIC Conference. XoveTIC 2022, vol 14, pages 111--114

Links:
BibTeX entry
@inproceedings{XoveTIC2022:Region_of_interest_bounded_COVID_19,
  author    = {Pl\textbackslash{}'acido Francisco Lizancos Vidal and Joaquim de Moura and Luc\textbackslash{}'ia Ramos and Jorge Novo and Marcos Ortega},
  title     = {Region of interest-bounded COVID-19 lung screening using images from portable X-ray devices},
  booktitle = {Proceedings of V XoveTIC Conference. XoveTIC 2022},
  editor    = {Alvaro Leitao and Luc\textbackslash{}'ia Ramos},
  series    = {Kalpa Publications in Computing},
  volume    = {14},
  pages     = {111--114},
  year      = {2023},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {https://easychair.org/publications/paper/gmvHG},
  doi       = {10.29007/cj6l}}
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