Chinese Medical Sciences Journal ›› 2019, Vol. 34 ›› Issue (2): 71-75.doi: 10.24920/003615

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人工智能赋能医学影像的现状与前景

史颖欢1,王乾2,*()   

  1. 1. 南京大学 计算机科学与技术系 计算机软件新技术国家重点实验室,南京 210023,中国
    2. 上海交通大学 生物医学工程学院 医学影像先进技术研究院,上海 200030,中国
  • 收稿日期:2019-03-31 接受日期:2019-05-20 出版日期:2019-06-11 发布日期:2019-06-11
  • 通讯作者: 王乾 E-mail:wang.qian@sjtu.edu.cn

The Artificial Intelligence-Enabled Medical Imaging: Today and Its Future

Shi Ying-huan1,Wang Qian2,*()   

  1. 1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China
    2. Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China
  • Received:2019-03-31 Accepted:2019-05-20 Online:2019-06-11 Published:2019-06-11
  • Contact: Wang Qian E-mail:wang.qian@sjtu.edu.cn

摘要:

目前,人工智能正在重塑医学成像技术并迅速发展。在本文中,我们评述了人工智能(Artificial intelligence, AI)赋能医学影像的最新进展。首先,简要回顾了人工智能演进的相关背景;然后,我们讨论了近年来人工智能在医学成像领域取得的成果,特别是在图像分割、配准、检测和识别等方面。此外,我们还介绍了几个具有代表性的 AI支持的医学成像应用场景,包括胸部 CT的肺结节,神经影像学和乳腺X线摄影等。AI在这些方面的应用表现出其在医学实践活动中应用的优势。最后,我们报告了人机交互的方式。我们认为,在未来的发展中,AI不仅会改变传统医学成像和图像阅读方式,也将改变当前的常规诊疗模式,并且介入到医疗领域的其他方面。

关键词: 医学影像, 人工智能, 机器学习, 深度学习, 图像分割, 图像配准, 图像检测, 图像识别

Abstract:

Medical imaging is now being reshaped by artificial intelligence (AI) and progressing rapidly toward future. In this article, we review the recent progress of AI-enabled medical imaging. Firstly, we briefly review the background about AI in its way of evolution. Then, we discuss the recent successes of AI in different medical imaging tasks, especially in image segmentation, registration, detection and recognition. Also, we illustrate several representative applications of AI-enabled medical imaging to show its advantage in real scenario, which includes lung nodule in chest CT, neuroimaging, mammography, and etc. Finally, we report the way of human-machine interaction. We believe that, in the future, AI will not only change the traditional way of medical imaging, but also improve the clinical routines of medical care and enable many aspects of the medical society.

Key words: medical imaging, artificial intelligence, deep learning, image segmentation, image registration, image detection, image recognition

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