Using deep convolutional neural network to diagnose covid-19 disease from CT scan images

Subject Areas : International Journal of Decision Intelligence

rezvaneh azizi ^{1 *} , hamid abbasi ²

1 - Department of Computer Engineering, Damghan Branch, Islamic Azad University, Damghan, Iran
2 - Department of Computer Engineering, Damghan Branch, Islamic Azad University, Damghan, Iran

Received: 2024-09-10 Accepted : 2025-01-29 Published : 2025-02-04

Keywords: CT scan images, convolutional neural network, Covid-19, modeling, deep learning,

Abstract :

 This paper examines the application of soft computing techniques in detecting COVID-19 through CT scan image analysis. Convolutional deep learning models are employed, and their performance in disease detection is evaluated. In this study, we investigate the optimization of feature extraction methods from CT scan images and present the results of our experiments. We focus on designing a COVID-19 detection system using a convolutional neural network model supported by open-source software such as Keras, Python, Google Colab, Kaggle, and Visual Studio. The results of this study indicate that using deep convolutional networks with layered architecture can significantly enhance the accuracy of COVID-19 detection through CT scan images and be effective in faster and more accurate patient diagnosis.The results of this study show that the use of deep convolutional networks in image processing provides us with significantly high accuracy and it is possible to improve the diagnosis of Covid-19 from these images with appropriate layering 

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