利用HOG图像特征和人工智能分类器诊断x射线图像中的COVID-19

Faten F. Kharbat, Tarik Elamsy, Nuha Hamada
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引用次数: 1

摘要

新型冠状病毒(COVID-19)正在以惊人的速度在全球蔓延,与SARS或MERS相比,感染和死亡人数更多。在缺乏针对COVID-19的特异性疫苗的情况下,COVID-19疾病的早期诊断对于疾病治疗和控制至关重要。最近的研究表明,与官方实验室RT-PCR检测相比,医学放射成像可能是一种更可靠、更实用、更快速的诊断和评估COVID-19的方法,特别是在缺乏医疗专业人员的情况下。在本文中,我们研究了人工智能和数据挖掘技术的帮助下,从胸部x射线医学图像中自动诊断COVID-19的任务。得到的结果是有希望的,比以前发表的结果要好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnosing COVID-19 in X-ray Images Using HOG Image Feature and Artificial Intelligence Classifiers
The novel coronavirus (COVID-19) pandemic is spreading across the globe at an alarming rate causing more infections and deaths in comparison to SARS or MERS. In the absence of specific vaccines for theCOVID-19, the early diagnosis of COVID-19 disease is crucial for disease treatment and control. Recent researches have shown that Medical Radiology imaging may be a more reliable, practical, and rapid method to diagnose and assess COVID-19 in comparison to the official laboratory RT-PCR tests, especially with the lack of medical professionals. In this article, we investigate the aid of Artificial Intelligence and Data Mining techniques to automate the task of diagnosing COVID-19 from Chest X-Rays medical images. The results obtained are promising and are better than previous results published earlier.
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