Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy.
Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy; Institute for Informatics and Telematics, National Research Council of Italy (CNR), Pisa, Italy.
Comput Methods Programs Biomed. 2020 Nov;196:105608. doi: 10.1016/j.cmpb.2020.105608. Epub 2020 Jun 20.
Coronavirus disease (COVID-19) is an infectious disease caused by a new virus never identified before in humans. This virus causes respiratory disease (for instance, flu) with symptoms such as cough, fever and, in severe cases, pneumonia. The test to detect the presence of this virus in humans is performed on sputum or blood samples and the outcome is generally available within a few hours or, at most, days. Analysing biomedical imaging the patient shows signs of pneumonia. In this paper, with the aim of providing a fully automatic and faster diagnosis, we propose the adoption of deep learning for COVID-19 detection from X-rays.
In particular, we propose an approach composed by three phases: the first one to detect if in a chest X-ray there is the presence of a pneumonia. The second one to discern between COVID-19 and pneumonia. The last step is aimed to localise the areas in the X-ray symptomatic of the COVID-19 presence.
Experimental analysis on 6,523 chest X-rays belonging to different institutions demonstrated the effectiveness of the proposed approach, with an average time for COVID-19 detection of approximately 2.5 seconds and an average accuracy equal to 0.97.
由一种新型人类从未识别过的病毒引起的传染病被称为冠状病毒病（COVID-19）。该病毒会引起呼吸道疾病（例如流感），症状包括咳嗽、发热，在严重情况下会引起肺炎。用于检测人类体内是否存在这种病毒的方法是对痰液或血液样本进行检测，结果通常在数小时内，或最多在数天内得出。对患者的生物医学影像进行分析会显示出肺炎的迹象。在本文中，我们旨在提供一种全自动且更快的诊断方法，因此提出采用深度学习技术从 X 光片中检测 COVID-19。
具体而言，我们提出了一种由三个阶段组成的方法：第一个阶段是检测胸部 X 光片中是否存在肺炎。第二个阶段是区分 COVID-19 和肺炎。最后一个步骤旨在定位 X 光片中 COVID-19 存在的症状区域。
对来自不同机构的 6523 张胸部 X 光片进行的实验分析证明了所提出方法的有效性，COVID-19 检测的平均时间约为 2.5 秒，平均准确率等于 0.97。
