A new composite approach for COVID-19 detection in X-ray images using deep features

ÖZCAN T.

APPLIED SOFT COMPUTING, vol.111, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 111
  • Publication Date: 2021
  • Doi Number: 10.1016/j.asoc.2021.107669
  • Journal Name: APPLIED SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Keywords: COVID-19 detection in X-ray images, Pre-trained models, Feature extraction, Deep features, Feature fusion, Data processing, OPTIMIZATION, RECOGNITION, FUSION
  • Erciyes University Affiliated: Yes

Abstract

The new type of coronavirus, COVID 19, appeared in China at the end of 2019. It has become a pandemic that is spreading all over the world in a very short time. The detection of this disease, which has serious health and socio-economic damages, is of vital importance. COVID-19 detection is performed by applying PCR and serological tests. Additionally, COVID detection is possible using X-ray and computed tomography images. Disease detection has an important position in scientific researches that includes artificial intelligence methods.