| 摘要: |
| 深度神经网络是新一代人工智能技术，其在自然语言处理、学习能力、计算机视觉上将机器的认知能力推向了新的高度。目前，深度神经网络在医学影像中的应用主要集中在发现异常、量化测量和鉴别诊断3个方面，基于深度神经网络的医学影像研究已涉及放射影像、病理图像、超声影像、内镜影像等多个领域。深度神经网络在一些任务场景中已展现出与医师相当甚至超越医师的表现。在人工智能技术高速发展的大环境下，医师群体应客观冷静地看待技术、科学严谨地评价技术、积极开放地参与技术的提升与应用，成为技术的驾驭者，走向人工智能技术辅助下的医疗服务未来。 |
| 关键词: 人工智能 医学影像 深度神经网络 发现异常 量化测量 鉴别诊断 |
| DOI：10.16781/j.0258-879x.2018.08.0813 |
| 投稿时间：2018-07-11修订日期：2018-08-02 |
| 基金项目:国家重点研发计划政府间项目（2016YFE0103000），上海市科学技术委员会基金项目（17411952400），上海市卫生计划生育委员会智慧医疗项目（2018ZHYL0101）. |
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| Discussion of artificial intelligence application in medical imaging |
| XIAO Yi1,XIA Chen2,ZHANG Rong-guo2,LIU Shi-yuan1* |
(1. Department of Radiology, Changzheng Hospital, Navy Medical University(Second Military Medical University), Shanghai 200003, China;
2. Advanced Institute of Beijing Infervision, Beijing 100080, China
*Corresponding author) |
| Abstract: |
| As a new generation of artificial intelligence technology, the deep neural network takes the cognitive ability of machine to a historical high level in natural language processing, learning ability and computer vision. At present, the application of deep neural network in medical imaging can be categorized into discovery of anomalies, quantitative measurement, and differential diagnosis. Medical imaging research based on deep neural network research has involved various medical imaging domains such as radiological imaging, pathological images, ultrasound imaging, and endoscopic imaging. In several tasks, deep neural network has demonstrated physician-level or even above-physician-level performance. In the context of rapid development of artificial intelligence in imaging medicine, physicians should adopt a more objective, scientific, and proactive attitude towards artificial intelligence technology, and become the masters of artificial intelligence technology and the creators of a futuristic medical world assisted by artificial intelligence technology. |
| Key words: artificial intelligence medical imaging deep neural network discovery of anomalies quantitative measurements differential diagnosis |
