机器学习在 COVID-19 肺炎 CT 图像和 X 射线中的应用。
Application of machine learning in CT images and X-rays of COVID-19 pneumonia.
机构信息
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
出版信息
Medicine (Baltimore). 2021 Sep 10;100(36):e26855. doi: 10.1097/MD.0000000000026855.
Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentation, diagnosis, and evaluation. Artificial intelligence can accurately segment infected parts in X-ray and CT images, assist doctors in improving diagnosis efficiency, and facilitate the subsequent assessment of the severity of the patient infection. The medical assistant platform based on machine learning can help radiologists make clinical decisions and helper in screening, diagnosis, and treatment. By providing scientific methods for image recognition, segmentation, and evaluation, we summarized the latest developments in the application of artificial intelligence in COVID-19 lung imaging, and provided guidance and inspiration to researchers and doctors who are fighting the COVID-19 virus.
冠状病毒病（COVID-19）已在全球范围内传播。X 射线和计算机断层扫描（CT）是两种广泛应用于图像采集、分割、诊断和评估的技术。人工智能可以准确地分割 X 射线和 CT 图像中的感染部位，帮助医生提高诊断效率，并便于后续评估患者感染的严重程度。基于机器学习的医疗辅助平台可以帮助放射科医生做出临床决策，并在筛选、诊断和治疗方面提供帮助。通过为图像识别、分割和评估提供科学方法，我们总结了人工智能在 COVID-19 肺部成像中的最新应用进展，为抗击 COVID-19 病毒的研究人员和医生提供了指导和启示。
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