• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

人工智能赋能的医学成像:现状与未来。

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

作者信息

Shi Ying-Huan, Wang Qian

机构信息

State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China.

Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.

出版信息

Chin Med Sci J. 2019 Jun 30;34(2):71-75. doi: 10.24920/003615.

DOI:10.24920/003615
PMID:31315746
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.

摘要

医学成像如今正被人工智能(AI)重塑,并正迅速迈向未来。在本文中,我们回顾了人工智能赋能医学成像的最新进展。首先,我们简要回顾人工智能在其发展历程中的背景。然后,我们讨论人工智能在不同医学成像任务中的近期成功案例,特别是在图像分割、配准、检测和识别方面。此外,我们举例说明人工智能赋能医学成像的几个代表性应用,以展示其在实际场景中的优势,其中包括胸部CT中的肺结节、神经成像、乳腺X线摄影等。最后,我们报告人机交互的方式。我们相信,在未来,人工智能不仅会改变传统的医学成像方式,还会改善医疗护理的临床流程,并推动医学领域的诸多方面发展。

相似文献

1
The Artificial Intelligence-Enabled Medical Imaging: Today and Its Future.人工智能赋能的医学成像:现状与未来。
Chin Med Sci J. 2019 Jun 30;34(2):71-75. doi: 10.24920/003615.
2
Artificial intelligence in medical imaging of the liver.人工智能在肝脏医学影像中的应用。
World J Gastroenterol. 2019 Feb 14;25(6):672-682. doi: 10.3748/wjg.v25.i6.672.
3
Potentials of AI in medical image analysis in Gastroenterology and Hepatology.人工智能在胃肠病学和肝病学医学影像分析中的应用潜力。
J Gastroenterol Hepatol. 2021 Jan;36(1):31-38. doi: 10.1111/jgh.15327.
4
Artificial Intelligence Pertaining to Cardiothoracic Imaging and Patient Care: Beyond Image Interpretation.人工智能在心胸影像学和患者护理中的应用:超越图像解读。
J Thorac Imaging. 2020 May;35(3):137-142. doi: 10.1097/RTI.0000000000000486.
5
Artificial intelligence in medical imaging.医学影像中的人工智能。
Magn Reson Imaging. 2020 May;68:A1-A4. doi: 10.1016/j.mri.2019.12.006. Epub 2019 Dec 16.
6
Collaborations of Industry, Academia, Research and Application Improve the Healthy Development of Medical Imaging Artificial Intelligence Industry in China.产学研用协同合作推动我国医学影像人工智能产业健康发展。
Chin Med Sci J. 2019 Jun 30;34(2):84-88. doi: 10.24920/003619.
7
Future Directions in Artificial Intelligence.人工智能的未来方向。
Radiol Clin North Am. 2021 Nov;59(6):1085-1095. doi: 10.1016/j.rcl.2021.07.008.
8
An Intelligent Future for Medical Imaging: A Market Outlook on Artificial Intelligence for Medical Imaging.医学成像的智能未来:医学成像中人工智能的市场展望。
J Am Coll Radiol. 2020 Jan;17(1 Pt B):165-170. doi: 10.1016/j.jacr.2019.07.019.
9
Artificial Intelligence in Intracoronary Imaging.冠状动脉内影像学中的人工智能。
Curr Cardiol Rep. 2020 May 29;22(7):46. doi: 10.1007/s11886-020-01299-w.
10
Artificial Intelligence and Stroke Imaging: A West Coast Perspective.人工智能与卒中影像:西海岸视角。
Neuroimaging Clin N Am. 2020 Nov;30(4):479-492. doi: 10.1016/j.nic.2020.07.001. Epub 2020 Sep 18.

引用本文的文献

1
A comprehensive dataset of germinoma on MRI/CT with clinical and radiomic data.一个包含生殖细胞瘤MRI/CT图像以及临床和影像组学数据的综合数据集。
Sci Data. 2025 Feb 21;12(1):312. doi: 10.1038/s41597-025-04596-7.
2
The value of deep learning-based computer aided diagnostic system in improving diagnostic performance of rib fractures in acute blunt trauma.深度学习辅助计算机辅助诊断系统在提高急性钝性创伤性肋骨骨折诊断性能中的价值。
BMC Med Imaging. 2023 Apr 13;23(1):55. doi: 10.1186/s12880-023-01012-7.
3
Research on Ultrasonic Image Recognition Based on Optimization Immune Algorithm.
基于优化免疫算法的超声图像识别研究。
Comput Math Methods Med. 2021 May 17;2021:5868949. doi: 10.1155/2021/5868949. eCollection 2021.