上海交通大学学报（医学版）

上海交通大学学报（医学版） >

2021 , Vol. 41 >Issue 2: 262 - 266

DOI: https://doi.org/10.3969/j.issn.1674-8115.2021.02.022

综述

人工智能技术在骨肌系统影像学方面的应用

  • 李小敏 ,
  • 曲扬 ,
  • 张少霆 ,
  • 赵亮 ,
  • 刘畅 ,
  • 谢帅宁 ,
  • 戴尅戎 ,
  • 艾松涛
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  • 1.上海交通大学医学院附属第九人民医院放射科，上海 200011
    2.上海商汤智能科技有限公司，上海 200030
    3.上海交通大学医学院附属第九人民医院骨科，上海 200011
李小敏（1994—），女，硕士生；电子信箱：lxm549496172@163.com。

收稿日期: 2020-07-05

  网络出版日期: 2021-02-28

基金资助

上海市科学技术委员会科研计划项目(19441902700);上海市教育委员会高峰高原学科建设计划(20152221);上海交通大学医工交叉面上项目(YG2017MS03)

收起

Overview of the application of artificial intelligence to radiology of the musculoskeletal system

  • Xiao-min LI ,
  • Yang QU ,
  • Shao-ting ZHANG ,
  • Liang ZHAO ,
  • Chang LIU ,
  • Shuai-ning XIE ,
  • Ke-rong DAI ,
  • Song-tao AI
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  • 1.Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
    2.Shanghai Sensetime Intelligent Technology Co. , Ltd, Shanghai 200030, China
    3.Department of Orthopaedics, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China

Received date: 2020-07-05

  Online published: 2021-02-28

Supported by

Scientific Research Project of Shanghai Science and Technology Commission(19441902700);Shanghai Municipal Education Commission—Gaofeng Clinical Medicine Grant Support(20152221);Shanghai Jiao Tong University Medical Engineering Cross Grant(YG2017MS03)

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摘要

骨肌系统疾病种类繁多，影像学检查是疾病诊断的首要手段。合理选择图像后处理方法，可为疾病的诊断、手术治疗以及预后等提供可靠的评估依据。人工智能技术作为计算机科学发展的新阶段，能够高效、精准地对影像学图像进行预处理和分析，辅助医师诊断和治疗工作，将为骨肌系统影像学领域的发展带来新的机遇。该文就人工智能在骨肌系统疾病的影像诊断方面的应用现状和挑战展开综述，以期为开展相关研究的学者提供一定的参考。

关键词： 骨肌系统; 影像诊断; 人工智能; 深度学习

本文引用格式

李小敏 , 曲扬 , 张少霆 , 赵亮 , 刘畅 , 谢帅宁 , 戴尅戎 , 艾松涛 . 人工智能技术在骨肌系统影像学方面的应用[J]. 上海交通大学学报（医学版）, 2021 , 41(2) : 262 -266 . DOI: 10.3969/j.issn.1674-8115.2021.02.022

Abstract

Musculoskeletal diseases are diverse. Medical imaging examination is the primary means of disease diagnosis. Reasonable selection of image post-processing methods can provide reliable evaluation basis for disease diagnosis, surgery and prognosis. As a new stage of the development of computer science, artificial intelligence technology can efficiently and accurately preprocess and analyze images, and assist clinicians in diagnosis and treatment. It will bring new opportunities for the development of musculoskeletal imaging. This paper reviews the current situation and challenges of artificial intelligence in the field of imaging diagnosis of musculoskeletal system diseases, in order to provide some reference for the relevant research scholars.

Key words： musculoskeletal system; imaging diagnosis; artificial intelligence; deep-learning

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