Detection and Classification of COVID‑۱۹ by Lungs Computed Tomography Scan Image Processing using Intelligence Algorithm
Publish place: Journal of medical signals and sensors، Vol: 11، Issue: 4
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JMSI-11-4_007
تاریخ نمایه سازی: 28 تیر 1402
Abstract:
The latest World Health Organization statistics show that the number of people living with COVID‑۱۹
disease is now more than ۴۲ 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‑۱۹ 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 ۷۹ participants. To
do this, in this article, for processing CT‑scan images of the lungs to diagnose and classification of
the COVID‑۱۹ 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‑۱۹) with high detection and classification accuracy. The algorithm presented in
this article has accurately identified the data of healthy subjects and patients with coronavirus.
Keywords:
Authors
Naser Safdarian
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University
Nader Jafarnia Dabanloo
Engineering Research Center in Medicine and Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran