Implementation of CNN based COVID-19 classification model from CT images

Creative Commons License

Kaya A., Atas K., Myderrizi I.

19th IEEE World Symposium on Applied Machine Intelligence and Informatics, SAMI 2021, Herl�any, Slovakya, 21 - 23 Ocak 2021, ss.201-206 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/sami50585.2021.9378646
  • Basıldığı Şehir: Herl�any
  • Basıldığı Ülke: Slovakya
  • Sayfa Sayıları: ss.201-206
  • Anahtar Kelimeler: Classification, Computed Tomography, Covid-19, Deep Learning
  • İstanbul Gelişim Üniversitesi Adresli: Evet

Özet

© 2021 IEEE.The number of COVID-19 patients around the globe is increasing day by day. Statistics show that even after almost 10 months from outbreak, number of the total patients has not reached to its peak value yet. Easy spreading of the virus among people causes high number of patients at the same time. Accelerating the reduction in spread is of vital importance. In order to achieve this reduction, early diagnosis of the disease and the number of tests and scans to be performed frequently becomes important. In this paper, a comprehensive model examination is made to overcome COVID-19 diagnosing problem. Using CT images, data augmentation technique is applied first in the pre-processing section and then pre-trained deep CNN networks perform the classification. The model is tested using various networks and high accuracy results of 96.5% and 97.9% are obtained for VGG-16 and EfficientNetB3 networks, respectively.