This study aims to investigate an automated approach using Convolutional Neural Network (CNN) to efficiently classify COVID-19 cases vs healthy cases using chest CT images. Convolutional Neural Network (CNN) is a class of deep neural networks, usually applied to analyzing image data, and can learn features effectively from images in comparison to the traditional method with image segmentation, feature extraction/selection and classification steps. Several models using pre-trained weights, including VGG16, VGG19, InceptionV3, InceptionResNetV2, Xception, DenseNet121, DenseNet169, and DenseNet201 were investigated. Overfitting was handled by randomly dropping nodes during training, augmenting training data, as well as using the validation set. We concluded that a CNN approach can detect COVID-19 using CT features, and DenseNet201is the highest performing model.
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