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Shah V, Keniya R, Shridharani A, et al. Diagnosis of COVID-19 using CT scan images and deep learning techniques. Emerg Radiol. 2021;28(3):497-505doi: 10.1007/s10140-020-01886-y.
Shah, V., Keniya, R., Shridharani, A., Punjabi, M., Shah, J., & Mehendale, N. (2021). Diagnosis of COVID-19 using CT scan images and deep learning techniques. Emergency radiology, 28(3), 497-505. https://doi.org/10.1007/s10140-020-01886-y
Shah, Vruddhi, et al. "Diagnosis of COVID-19 using CT scan images and deep learning techniques." Emergency radiology vol. 28,3 (2021): 497-505. doi: https://doi.org/10.1007/s10140-020-01886-y
Shah V, Keniya R, Shridharani A, Punjabi M, Shah J, Mehendale N. Diagnosis of COVID-19 using CT scan images and deep learning techniques. Emerg Radiol. 2021 Jun;28(3):497-505. doi: 10.1007/s10140-020-01886-y. Epub 2021 Feb 01. PMID: 33523309; PMCID: PMC7848247.
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Emerg Radiol. 2021 Jun;28(3):497-505. doi: 10.1007/s10140-020-01886-y. Epub 2021 Feb 01.

Diagnosis of COVID-19 using CT scan images and deep learning techniques.

Emergency radiology

Vruddhi Shah, Rinkal Keniya, Akanksha Shridharani, Manav Punjabi, Jainam Shah, Ninad Mehendale

Affiliations

  1. K. J. Somaiya College of Engineering, Somaiya Vidyavihar University, Vidyavihar, Mumbai, 400077, India.
  2. K. J. Somaiya College of Engineering, Somaiya Vidyavihar University, Vidyavihar, Mumbai, 400077, India. [email protected].

PMID: 33523309 PMCID: PMC7848247 DOI: 10.1007/s10140-020-01886-y

Abstract

Early diagnosis of the coronavirus disease in 2019 (COVID-19) is essential for controlling this pandemic. COVID-19 has been spreading rapidly all over the world. There is no vaccine available for this virus yet. Fast and accurate COVID-19 screening is possible using computed tomography (CT) scan images. The deep learning techniques used in the proposed method is based on a convolutional neural network (CNN). Our manuscript focuses on differentiating the CT scan images of COVID-19 and non-COVID 19 CT using different deep learning techniques. A self-developed model named CTnet-10 was designed for the COVID-19 diagnosis, having an accuracy of 82.1%. Also, other models that we tested are DenseNet-169, VGG-16, ResNet-50, InceptionV3, and VGG-19. The VGG-19 proved to be superior with an accuracy of 94.52% as compared to all other deep learning models. Automated diagnosis of COVID-19 from the CT scan pictures can be used by the doctors as a quick and efficient method for COVID-19 screening.

Keywords: COVID-19; CT scan; Diagnosis using deep learning

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