Analysis of chest X-Ray (CXR) images in COVID-19 patients based on age using the Otsu thresholding segmentation method

Uhty Maesyaroh, Laelatul Munawaroh, Heni Sumarti, R. Adrial
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Abstract

The infection with the COVID-19 virus or better known as the Corona virus spread throughout China and other countries around the world until it was designated a pandemic by the World Health Organization (WHO). Detection of patients infected with COVID-19 in the form of RT-PCR, CT-Scan images and Chest X-Ray (CXR). This study aims to analyze CXR images of COVID-19 patients based on age using Otsu Thresholding Segmentation. The image segmentation process uses the Otsu auto-tresholding method to separate objects from the background on the CXR image. The results show that the images of COVID-19 patients have pneumonia spots that are not visible on the original CXR image. The average value of the accuracy of the Otsu Thresholding results is 95.18%. Penunomia spots are mostly found in COVID-19 patients aged 50 to 70 years and over which cause severe lung damage.©2021 JNSMR UIN Walisongo. All rights reserved.
基于年龄的新型冠状病毒肺炎患者胸部x线图像Otsu阈值分割分析
COVID-19病毒或更广为人知的冠状病毒感染在中国和世界其他国家蔓延,直到世界卫生组织(世卫组织)将其确定为大流行。利用RT-PCR、ct扫描图像和胸部x线(CXR)检测COVID-19患者。本研究旨在利用Otsu阈值分割对基于年龄的COVID-19患者的CXR图像进行分析。图像分割过程使用Otsu自动阈值法将CXR图像上的目标与背景分离。结果表明,新冠肺炎患者的图像存在原CXR图像上不可见的肺炎斑点。Otsu阈值结果的准确率平均值为95.18%。Penunomia斑点多见于50 ~ 70岁以上的新冠肺炎患者,会造成严重的肺损伤。©2021 JNSMR UIN Walisongo。版权所有。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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