基于胸部CT图像的COVID-19无监督检测方法

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI:10.1109/R10-HTC53172.2021.9641513

Prashanth S, K. Devika, V. R. Murthy Oruganti

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引用次数: 2

摘要

在这项工作中，我们假设我们有正常(健康)和一般肺炎感染受试者的数据。基于这些知识，我们是否可以将COVID-19感染预测为异常健康状况?如果有，感染的严重程度是什么?这项研究将有助于确定COVID-19的新变异、突变为异常健康状况。从长远来看，我们的研究可以根据健康受试者本身的数据帮助识别新的感染。

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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An Unsupervised Approach for COVID-19 Detection using Chest CT Images

In this work we assume we have data of normal (healthy) and general pneumonia infected subjects. Based on this knowledge, can we predict COVID-19 infection as abnormal health condition? If so what is the severity of infection? This study will help identify new variants, mutations of COVID-19 as abnormal health conditions. In long term, our study can help identify new infections altogether based on data of healthy subjects itself.

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来源期刊

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)

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