Detection of COVID-19 Based on Chest Medical Imaging and Artificial Intelligence Techniques

Alwash, Nawres A.; Kareem, Hussain

doi:10.30684/etj.v39i10.2200

	Detection of COVID-19 Based on Chest Medical Imaging and Artificial Intelligence Techniques
Engineering and Technology Journal
Article 13, Volume 39, Issue 10, 2021, Pages 1588-1600 PDF (1.19 M)
Document Type: Research Paper
DOI: 10.30684/etj.v39i10.2200
Authors
Nawres A. Alwash^* ; Hussain Kareem
Electrical Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.
Abstract
The emergence of COVID-19 disease in the world has moved the wheel of scientific research in order to detect it in the best method, and the fastest of these methods is the use of Artificial Intelligence (AI) techniques to help medical professionals detect COVID-19. The proposed topic is aim to develop algorithm based on combination between imageprocessing techniques with artificial intelligence to diagnose COVID-19. The proposed algorithm consists of five stages to detect and classify COVID-19 from Computer Tomography (CT) images. These stages include; The first of these stages is to collect data from hospitals as real data and from Kagglewebsite for patients and healthy people, then the stage before removing the noise and converting it from RGB to grayscale, then we improve the image, segmentation and formalities, the other stage is a stage used to extract the important characteristics, and the last stage is the classification of images CT scan using Feed Forward Back Propagation Network (FFBPN) and Support Vector Machine (SVM )and compare the result between them and see if the person is infected or healthy. This study was implemented in MATLAB software. The results showed that the noise cancellation technology using anisotropic filtering gave the best results. As for the optimization technology, only the brightness of the images has been increased. At the stage of segmentation of the area of lung injection using the area transplant method, the best results are detection of COVID-19 from other healthy tissues. The FFBPN gave the best results for detecting and classifying COVID-19 as well as determining whether a person has been infected or not. The results of the proposed methodology in accurate and rapid detection of COVID-19 in the lung. The contribution of this paper is to help medical staff detect COVID-19 without human intervention.
Highlights
Detection of COVID-19 was studied. Classification of images CT scan using Feed Forward Back Propagation Network (FFBPN) and Support Vector Machine (SVM) was implemented. SVM gives 96% accuracy and FFBPN gives 98.5% accuracy.
Keywords
artificial intelligence; Covid_19; Medical Imaging; FFBPN; SVM

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