Early pleural effusion detection from respiratory diseases including COVID-19 via deep learning

Sertan Serte, Ali Serener
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引用次数: 6

Abstract

Pleural effusion is the build-up of excess fluid between the pleura layers around the lung. This fluid may be transudative or exudative. Pneumonia and cancer are common exudative causes of pleural effusion. Other causes include tuberculosis and recently discovered COVID-19. Physicians are able to diagnose pleural effusion through the use of chest radiographs. In this work, we propose, instead, the early detection of pleural effusion from tuberculosis, pneumonia, and COVID-19 diseases on chest radiographs using deep learning. The performance results show that the early detection of pleural effusion from pneumonia and tuberculosis have the highest accuracy. They further show that the deep learning architecture can distinguish bacterial pneumonia and COVID-19 diseases from pleural effusion the best.
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基于深度学习的COVID-19等呼吸系统疾病早期胸腔积液检测
胸膜积液是肺周围胸膜层之间积聚的过量液体。这种液体可能是分泌性的或渗出的。肺炎和癌症是胸腔积液的常见原因。其他原因包括结核病和最近发现的COVID-19。医生可以通过胸片诊断胸腔积液。在这项工作中,我们建议使用深度学习在胸片上早期发现结核病、肺炎和COVID-19疾病引起的胸腔积液。性能结果表明,早期发现肺炎和肺结核胸腔积液的准确率最高。他们进一步表明,深度学习架构可以最好地区分细菌性肺炎和COVID-19疾病与胸腔积液。
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