胸部x线检测COVID-19

Ganesh Yadav, Shobhit Jain, Shikhar Singh, Shivam Shanna
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引用次数: 3

摘要

为了加快COVID-19病因的发现,本研究利用深度卷积神经网络(CNN)开发了新型诊断平台,帮助中摩医院放射科医师诊断患者的COVID-19肺炎和非COVID-19肺炎。顾名思义,我们研究的关键目标是开发一种胸部x线图像分类程序,该程序可以正确地识别扫描的分类为“正常”、“病毒性肺炎”或“COVID-19”。使用x射线,我们将训练一个图像分类器来确定一个人是否患有COVID-19。在这个数据集中,有3000多张胸部x线照片被分类为正常、病毒和COVID-19。一个图像分类系统,适当地识别哪一个类别的胸部x线扫描对应的是这个调查的目的。
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DETECTION OF COVID-19 WITH CHEST X-RAY
In order to speed up finding of causes of COVID-19 illness, this study developed novel diagnostic platform using profound convolutional neural network (CNN) helping radiologists diagnose COVID-19 pneumonia beside non-COVID-19 pneumonia in patient in Middle more Hospital. As the name suggests, crucial objective of our research is to produce a chest X-ray image classification program which could properly identify a scan's categorization as either "normal," "viral pneumonia," or "COVID-19." Using X-rays, we will train an image classifier to determine whether or not a person has COVID-19. In this data set, there are over 3000 chest X-ray pictures categorized in normal, viral, as well as COVID-19. A picture classifying system which properly identifies which of three categories Chest X-Ray scan corresponds with is purpose of this investigation.
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