Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images

Year 2022, Volume: 11 Issue: 2, 36 - 42, 29.06.2022

Bekir Aksoy , Osamah Khaled Musleh Salman

https://doi.org/10.46810/tdfd.1095624

Cited By: 2

Abstract

Many pandemics have caused the deaths of millions of people in world history from past to present. Therefore, the measures to be taken in the prevention of pandemics are of great importance. In addition to the precautions, it is very important to be able to diagnose the disease early. The most recent pandemic occurred in the world is the COVID-19 outbreak that emerged in China in late 2019. In this study, Computerized Tomography images of 746 patients taken from an open source (GitHub) website were used. Images were analyzed using the Resnet-101 model, which is one of the deep learning architectures. Classification process was carried out with the created Resnet-101 model. With the Resnet-101 model, individuals with Covid-19 disease were tried to be identified. The Resnet-101 model detected individuals with Covid-19 disease with an accuracy rate of 94.29%.

Keywords

Covid-19, Deep Learning, ResNet-101, Computerized Tomography Images

Thanks

We would like to thank Zhao et al. who opened the data set used in the study for open access.

Resnet-101 Derin Öğrenme Mimarisi ile Bilgisayarlı Tomografi Görüntüleri Kullanılarak Covid-19 Hastalığının Tahminlenmesi

Abstract

Geçmişten günümüze dünya tarihinde birçok salgın milyonlarca insanın ölümüne neden olmuştur. Bu nedenle salgınlardan korunmada alınacak önlemler büyük önem taşımaktadır. Önlemlere ek olarak, hastalığın erken teşhis edilebilmesi çok önemlidir. Dünyada en son yaşanan salgın 2019 yılının sonlarında Çin'de ortaya çıkan COVID-19 salgınıdır. Bu çalışmada 746 hastanın açık kaynaklı (GitHub) bir web sitesinden alınan Bilgisayarlı Tomografi görüntüleri kullanılmıştır. Görüntüler, derin öğrenme mimarilerinden Resnet-101 modeli kullanılarak analiz edilmiştir. Oluşturulan Resnet-101 modeli ile sınıflandırma işlemi gerçekleştirilmiştir. Resnet- 101 modeli ile Covid-19 hastalığı olan bireyler tespit edilmeye çalışılmıştır. Resnet-101 modeli, Covid-19 hastalığı olan bireyleri %94,29 doğruluk oranıyla tespit ettiği belirlenmiştir.

Keywords

Covid-19, Derin Öğrenme, ResNet-101, Bilgisayarlı Tomografi Görüntüleri

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