Application and Prospect of Deep Learning Technology in Medical Image Analysis

LIU Li-bing; FU Li-yao

doi:10.3969/j.issn.2096-6091.2024.01.005

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Application and Prospect of Deep Learning Technology in Medical Image Analysis

SURVEYS & TUTORIALS | 更新时间：2025-02-13

- Application and Prospect of Deep Learning Technology in Medical Image Analysis
- New Generation of Information Technology Vol. 7, Issue 1, Pages: 24-28(2024)
- 作者机构：
  
  重庆市信息通信咨询设计院有限公司，重庆 400041
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.2096-6091.2024.01.005
  CLC： TP399
- Published：25 January 2024，
- 稿件说明：
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刘立兵, 傅励瑶. 深度学习技术在医学影像分析中的应用与展望[J]. 新一代信息技术, 2024, 7(1): 24-28

LIU Li-bing, FU Li-yao. Application and Prospect of Deep Learning Technology in Medical Image Analysis[J]. New Generation of Information Technology, 2024, 7(1): 24-28
刘立兵, 傅励瑶. 深度学习技术在医学影像分析中的应用与展望[J]. 新一代信息技术, 2024, 7(1): 24-28 DOI： 10.3969/j.issn.2096-6091.2024.01.005.

LIU Li-bing, FU Li-yao. Application and Prospect of Deep Learning Technology in Medical Image Analysis[J]. New Generation of Information Technology, 2024, 7(1): 24-28 DOI： 10.3969/j.issn.2096-6091.2024.01.005.

摘要

深度学习在医学影像分割、配准和融合等方面取得了显著成果，应用实例包括计算机辅助诊断、个性化治疗和临床决策支持等。深度学习技术在医学影像分析中展现出巨大的潜力，极大地提升了医疗诊断的准确性和效率。本文讨论了深度学习在医学影像处理领域的主要技术发展及其应用，重点介绍了基于深度学习的分割、配准、融合和联邦学习方法在增强诊断准确性和辅助治疗中的关键作用。最后，本文探讨了当前技术的局限性以及未来的发展方向，旨在为医学影像处理领域的研究和应用提供有价值的参考。

Abstract

Deep learning technology has shown great potential in medical image analysis

greatly improving the accuracy and efficiency of medical diagnosis. This paper discusses the major technological developments and applications of deep learning in the field of medical image processing

with a focus on the key roles of deep learning based segmentation

registration

fusion

and federated learning methods in enhancing diagnostic accuracy and assisting treatment. Finally

this article explores the limitations of current technology and future development directions

aiming to provide valuable references for research and application in the field of medical image processing.

关键词

深度学习图像分析医学影像分析分析技术应用

Keywords

deep learningimage analysismedical imaging analysisapplication of analytical techniques

references

LECUN Y, BOTTOU L. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998, 86(11): 2278-2324.

VASWANI A, SHAZEER N M, PARMAR N, et al. Attention is all you need[J]. arXiv, 2017. DOI:10.48550/arXiv.1706.03762http://dx.doi.org/10.48550/arXiv.1706.03762.

MA J, HE Y T, LI F F, et al. Segment anything in medical imag-es[J]. Nature Communications, 2024, 15(1): 654.

余升林, 吴彤, 葛明锋, 等. 循环一致性的无监督可变形图像配准方法[J]. 计算机辅助设计与图形学学报, 2023, 35(4): 516-524.

黄渝萍, 李伟生. 医学图像融合方法综述[J]. 中国图象图形学报, 2023, 28(1): 118-143.

左艳, 黄钢, 聂生东. 深度学习在医学影像智能处理中的应用与挑战[J]. 中国图象图形学报, 2021, 26(2): 305-315.

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Related Institution

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