基于局部二值模式肺x线检测的新冠肺炎患者分类

Dhian Satria Yudha Kartika, Anita Wulansari, E. M. Safitri, Hendra Maulana, N. C. Wibowo
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引用次数: 0

摘要

Covid-19疫情造成的大量死亡以各种方式影响人们,包括经济和心理方面。以往的研究是对COVID-19患者的各种症状进行分析。病情严重的患者通常会在肺部发现一个白点。因此,胸部x线检查是检查患者的必要医学评估之一。这项研究的重点是通过分析患者的胸部x光照片来确定患者是否患有COVID-19。共使用864张x射线照片作为数据集。处理数据集的早期步骤包括去除噪声,均衡大小和提高精度值。采用局部二值模式(LBP)方法提取数据集特征。性能分析结果精密度为78.5%,召回率为78%,f-measure值为79%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification Of Covid Patients Based On Detection Of Lung X-Rays Using Local Binary Pattern Method
High number of deaths due to Covid-19 outbreak affect people in various ways including their economic and psychological side. Previous studies were carried out in analyzing various symptoms in COVID-19 patients. Patients in severe conditions are usually found with a white spot in their lungs. Therefore chest x-ray is one of the necessary medical assessment to examine the patients. This study focus on determining whether a patient suffered from COVID-19 by analyzing their chest X-rays photos. A total of 864 X-rays photos were used as a dataset. Earlier steps in processing the dataset included removing the noise, equalizing the size and increasing the accuracy value. The Local Binary Pattern (LBP) method was used to extract the dataset feature. The performance analysis result was a precision value of 78.5%, recall of 78%, and f-measure of 79%.
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