Table 2 List of CNNs used for the detection and classification of COVID-19
From: Convolutional neural networks for the diagnosis and prognosis of the coronavirus disease pandemic
Task | Image modality | Dataset | Approach | Reference |
|---|---|---|---|---|
Detection | X-ray | Normal, non-COVID-19 pneumonia, COVID-19 | COVID-Net, tailored deep CNN | Wang et al. [36] |
Detection | X-ray | Normal, viral, bacterial, COVID-19 | CovXNet, CNN with transfer learning | Mahmud et al. [37] |
Detection | X-ray | COVID-19, non-COVID-19 (includes normal and other pneumonia) | CNN-tailored shallow architecture, 5-fold cross-validation | Mukherjee et al. [38] |
Detection | X-ray | Normal, COVID-19 | ResNet50, InceptionV3 and Inception-ResNetV2, 5-fold cross-validation | Narin et al. [39] |
Detection | X-ray | Normal, COVID-19, bacterial pneumonia | Modality-specific transfer learning with CNN, iterative pruning, ensemble strategies | Rajaraman et al. [40] |
Detection | X-ray | COVID-19, non-COVID-19 pneumonia | ResNet50, VGG16, small CNN, ensemble of three CNNs, 10-fold cross-validation | Hall et al. [41] |
Detection | X-ray | Normal, pneumonia and COVID-19 | MobilNetV2 | Apostolopoulos and Mpesiana [42] |
Detection | X-ray | Normal, pneumonia and COVID-19 | Concatenation Xception and ResNet50V2 | Rahimzadeh and Attar [43] |
Detection | X-ray | Common pulmonary diseases, COVID-19 | MobileNetV2 | Apostolopoulos et al. [44] |
Detection | X-ray, CT scans | COVID-19, bacterial pneumonia, viral pneumonia | AlexNet, VGG, SqueezeNet, GoogLeNet, MobileNet, ResNet and DenseNet | Rehman et al. [45] |
Detection | CT scan | COVID-19 positive and negative | VGG16, InceptionV3, ResNet50, DenseNet121, DenseNet201, decision fusion | Mishra et al. [46] |
Classification | X-ray | Normal, COVID-19, pneumonia | ResNet152, SMOTE algorithm | Kumar et al. [47] |
Classification | X-ray | Normal, COVID-19 | COVIDX-Net, deep learning classifiers VGG16 and DenseNet201 showed good performance | Hemdan et al. [48] |
Classification | X-ray | Normal, SARS, COVID-19 | DeTraC, transfer learning, ResNet18 | Abbas et al. [49] |
Classification | X-ray | Normal, COVID-19, bacterial and viral pneumonia | Transfer learning with CNN | Ozturk et al. [50] |
Classification | CT scan | Image patches of COVID-19 findings, COVID-19 and no-finding | VGG16, GoogleNet, and ResNet50, feature fusion and ranking technique, SVM classifier | Özkaya et al. [51] |
Classification | CT scans | Viral pneumonia, COVID-19 | M-Inception, transfer learning | Wang et al. [52] |
Detection | X-ray | COVID-19, normal | CovidGAN, VGG16, GAN | Waheed et al. [53] |
Detection | X-ray | COVID-19, normal | AlexNet, ResNet18, SqueezeNet, GoogLeNet, GAN | Khalifa et al. [54] |
Classification | X-ray | COVID-19, normal, other pneumonia | VGG16, ResNet50, EfficientNetB0, GAN | Zebin and Rezvy [55] |