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   detection and classification of covid-19 by lungs computed tomography scan image processing using intelligence algorithm  
   
نویسنده safdarian naser ,jafarnia dabanloo nader
منبع journal of medical signals and sensors - 2021 - دوره : 11 - شماره : 4 - صفحه:274 -284
چکیده    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
کلیدواژه classification ,computerized tomography ,covid19 ,detection ,medical image processing
آدرس islamic azad university, science and research branch, department of biomedical engineering, iran, islamic azad university, science and research branch, engineering research center in medicine and biology, iran
پست الکترونیکی jafarnia@srbiau.ac.ir
 
   Detection and Classification of COVID-19 by Lungs Computed Tomography Scan Image Processing using Intelligence Algorithm  
   
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