Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.
National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
Clin Radiol. 2019 May;74(5):338-345. doi: 10.1016/j.crad.2018.12.015. Epub 2019 Jan 28.
Due to recent advances in artificial intelligence, there is renewed interest in automating interpretation of imaging tests. Chest radiographs are particularly interesting due to many factors: relatively inexpensive equipment, importance to public health, commonly performed throughout the world, and deceptively complex taking years to master. This article presents a brief introduction to artificial intelligence, reviews the progress to date in chest radiograph interpretation, and provides a snapshot of the available datasets and algorithms available to chest radiograph researchers. Finally, the limitations of artificial intelligence with respect to interpretation of imaging studies are discussed.
由于人工智能的最新进展，人们对自动化影像检查解读重新产生了兴趣。胸部 X 光片因其诸多因素而备受关注：设备相对便宜、对公共卫生很重要、在全球范围内广泛开展、看似复杂但需要多年时间才能掌握。本文简要介绍了人工智能，回顾了迄今为止在胸部 X 光片解读方面的进展，并提供了胸部 X 光片研究人员可用的数据集和算法的快照。最后，讨论了人工智能在影像研究解读方面的局限性。
