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Journal of Medical Signals and Sensors، جلد ۱۱، شماره ۴، صفحات ۲۷۴-۲۸۴
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عنوان انگلیسی Detection and Classification of COVID-19 by Lungs Computed Tomography Scan Image Processing using Intelligence Algorithm
چکیده انگلیسی مقاله The latest World Health Organization statistics show that the number of people living with COVID-19 disease is now more than 42 million worldwide. Some diagnosis methods include detecting and observing clinical symptoms associated with the disease (fever, dry cough, shortness of breath, sore throat, and muscle fatigue). Some other methods, such as computed tomography (CT)-scan imaging from the lungs, are the more accurate diagnostic methods. In this study, we examine the types of abnormal COVID-19 can cause in the lungs of infected subjects and detect and classify this disease. In this paper, we used data from the lung's CT-scan images from the 79 participants. To do this, in this article, for processing CT-scan images of the lungs to diagnose and classification of the COVID-19 disease in men and women of different ages, for rapid diagnosis and high accuracy of this disease by the automatic classification algorithm is used. The final results showed that the proposed method could base on different categories (gender, age categories, and type of damage caused by COVID-19) with high detection and classification accuracy. The algorithm presented in this article has accurately identified the data of healthy subjects and patients with coronavirus.
کلیدواژه‌های انگلیسی مقاله Classification, computerized tomography, COVID-19, detection, medical image processing
نویسندگان مقاله | Naser Safdarian
Engineering Research Center in Medicine and Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran


| Nader Jafarnia Dabanloo


نشانی اینترنتی http://jmss.mui.ac.ir/index.php/jmss/article/view/594
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Short Reports
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