Sedik Ahmed, Hammad Mohamed, Abd El-Samie Fathi E, Gupta Brij B, Abd El-Latif Ahmed A
Department of the Robotics and Intelligent Machines, Kafrelsheikh University, Kafrelsheikh, Egypt.
Information Technology Department, Faculty of Computers and Information, Menoufia University, Shebeen El-Kom, Egypt.
Neural Comput Appl. 2022;34(14):11423-11440. doi: 10.1007/s00521-020-05410-8. Epub 2021 Jan 19.
The new Coronavirus disease 2019 (COVID-19) is rapidly affecting the world population with statistics quickly falling out of date. Due to the limited availability of annotated Coronavirus X-ray and CT images, the detection of COVID-19 remains the biggest challenge in diagnosing this disease. This paper provides a promising solution by proposing a COVID-19 detection system based on deep learning. The proposed deep learning modalities are based on convolutional neural network (CNN) and convolutional long short-term memory (ConvLSTM). Two different datasets are adopted for the simulation of the proposed modalities. The first dataset includes a set of CT images, while the second dataset includes a set of X-ray images. Both of these datasets consist of two categories: COVID-19 and normal. In addition, COVID-19 and pneumonia image categories are classified in order to validate the proposed modalities. The proposed deep learning modalities are tested on both X-ray and CT images as well as a combined dataset that includes both types of images. They achieved an accuracy of 100% and an F1 score of 100% in some cases. The simulation results reveal that the proposed deep learning modalities can be considered and adopted for quick COVID-19 screening.
新型冠状病毒病2019（COVID-19）正在迅速影响全球人口，相关统计数据很快就过时了。由于带注释的冠状病毒X射线和CT图像数量有限，COVID-19的检测仍然是诊断这种疾病的最大挑战。本文通过提出一种基于深度学习的COVID-19检测系统，提供了一个很有前景的解决方案。所提出的深度学习模式基于卷积神经网络（CNN）和卷积长短期记忆网络（ConvLSTM）。采用两个不同的数据集对所提出的模式进行仿真。第一个数据集包括一组CT图像，而第二个数据集包括一组X射线图像。这两个数据集都由两类组成：COVID-19和正常。此外，对COVID-19和肺炎图像类别进行分类，以验证所提出的模式。所提出的深度学习模式在X射线和CT图像以及包含这两种图像类型的组合数据集上进行了测试。在某些情况下，它们的准确率达到了100%，F1分数也达到了100%。仿真结果表明，所提出的深度学习模式可用于快速的COVID-19筛查。
