Version 1
: Received: 19 August 2020 / Approved: 21 August 2020 / Online: 21 August 2020 (05:17:46 CEST)
How to cite:
Sethy, P.K.; Pandey, C.; Behera, S.K. Computer Aid Screening of COVID19 using X-ray and CT Scan Images: A Comparative Study. Preprints2020, 2020080472. https://doi.org/10.20944/preprints202008.0472.v1
Sethy, P.K.; Pandey, C.; Behera, S.K. Computer Aid Screening of COVID19 using X-ray and CT Scan Images: A Comparative Study. Preprints 2020, 2020080472. https://doi.org/10.20944/preprints202008.0472.v1
Sethy, P.K.; Pandey, C.; Behera, S.K. Computer Aid Screening of COVID19 using X-ray and CT Scan Images: A Comparative Study. Preprints2020, 2020080472. https://doi.org/10.20944/preprints202008.0472.v1
APA Style
Sethy, P.K., Pandey, C., & Behera, S.K. (2020). <strong>Computer Aid Screening of COVID19 using X-ray and CT Scan Images: A Comparative Study</strong>. Preprints. https://doi.org/10.20944/preprints202008.0472.v1
Chicago/Turabian Style
Sethy, P.K., Chanki Pandey and Santi Kumari Behera. 2020 "<strong>Computer Aid Screening of COVID19 using X-ray and CT Scan Images: A Comparative Study</strong>" Preprints. https://doi.org/10.20944/preprints202008.0472.v1
Abstract
In this article, we analyse the computer aid screening method of COVID19 using Xray and CT scan images. The main objective is to set an analytical closure about the computer aid screening of COVID19 among the X-ray image and CT scan image. The computer aid screening method includes deep feature extraction, transfer learning and traditional machine learning image classification approach. The deep feature extraction and transfer learning method considered 13 pre-trained CNN model. The machine learning approach includes three sets of features and three classifiers. The pre-trained CNN models are alexnet, googlenet, vgg16, vgg19, densenet201, resnet18, resnet50, resnet101, inceptionv3, inceptionresnetv2, xception, mobilenetv2 and shufflenet. The features and classifiers in machine learning approaches are GLCM, LBP, HOG and KNN, SVM, Naive bay’s respectively. In addition, we also analyse the different paradigms of classifiers. In total, the comparative analysis is carried out in 65 classification models, i.e. 13 in deep feature extraction, 13 in transfer learning and 39 in machine learning approaches. Finally, all the classification models perform better in X-ray image set compare to CT scan image set.
Keywords
Computer-aided Screening; Coronavirus; X-Ray; CT scan; Machine Learning; Transfer Learning; Deep Learning
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.