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


ÖZCAN T.

APPLIED SOFT COMPUTING, vol.111, 2021 (Journal Indexed in SCI) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 111
  • Publication Date: 2021
  • Doi Number: 10.1016/j.asoc.2021.107669
  • Title of Journal : APPLIED SOFT COMPUTING
  • Keywords: COVID-19 detection in X-ray images, Pre-trained models, Feature extraction, Deep features, Feature fusion, Data processing, OPTIMIZATION, RECOGNITION, FUSION

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.