Diagnosis of COVID-19 Disease Using Lung CT-scan Image Processing Techniques

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Introduction

Today, several methods are used for detecting COVID-19 such as disease-related clinical symptoms, and more accurate diagnostic methods like lung CT-scan imaging. This study aimed to achieve an accurate diagnostic method for intelligent and automatic diagnosis of COVID-19 using lung CT-scan image processing techniques and utilize the results of this method as an accurate diagnostic tool complementing the CT-scan devices.

Method

Based on digital image processing algorithms such as segmentation and feature extraction and using various methods of statistical analysis on the features extracted from images, CT-scan images of 79 male and female patients in different ages were analyzed and the effects of this disease on the infected lungs of patients were evaluated. This research was conducted in the spring of 2020 in the Faculty of Medical Sciences and Technologies, Science and Research Branch in Tehran.

Results

This intelligent method based on feature extraction from lung CT-scan images can diagnose COVID-19 with high accuracy on different categories (gender, type of injury caused by the disease). The analysis of lung tissue involvement in patients with COVID-19 revealed that most patients had tissue damage in the lower parts of both lungs to a greater extent than the middle and upper lung lobes.

Conclusion

The algorithm presented in this study can accurately detect and differentiate the data of images taken from the lungs of healthy people and patients with coronavirus disease.

Language:
Persian
Published:
Journal of Health and Biomedical Informatics, Volume:8 Issue: 1, 2021
Pages:
1 to 11
magiran.com/p2292017  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!