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基于深度学习的多模态医学影像研究进展

王宗敏 福林 高云玥

王宗敏, 福林, 高云玥. 基于深度学习的多模态医学影像研究进展[J]. 分子影像学杂志, 2022, 45(3): 459-464. doi: 10.12122/j.issn.1674-4500.2022.03.30
引用本文: 王宗敏, 福林, 高云玥. 基于深度学习的多模态医学影像研究进展[J]. 分子影像学杂志, 2022, 45(3): 459-464. doi: 10.12122/j.issn.1674-4500.2022.03.30
WANG Zongmin, FU Lin, GAO Yunyue. Research progress of multimodal medical imaging based on deep learning[J]. Journal of Molecular Imaging, 2022, 45(3): 459-464. doi: 10.12122/j.issn.1674-4500.2022.03.30
Citation: WANG Zongmin, FU Lin, GAO Yunyue. Research progress of multimodal medical imaging based on deep learning[J]. Journal of Molecular Imaging, 2022, 45(3): 459-464. doi: 10.12122/j.issn.1674-4500.2022.03.30

基于深度学习的多模态医学影像研究进展

doi: 10.12122/j.issn.1674-4500.2022.03.30
基金项目: 

内蒙古医科大学科技百万工程联合项目 YKD2018KJBW(LH)036

详细信息
    作者简介:

    王宗敏,在读硕士研究生,E-mail: 1559768938@qq.com

    通讯作者:

    福林,主任医师,E-mail: fulin200907@163.com

Research progress of multimodal medical imaging based on deep learning

  • 摘要: 凭借深度学习及大数据等技术的飞速发展,人工智能是医学领域最具发展前景的技术,鉴于医学影像对疾病的诊断与及时治疗的关键作用,医学影像与人工智能的结合正成为重要的交叉学科研究方向。在临床实践中,医生为了更精确全面的诊断疾病,往往需要同时参考多模态的影像数据进行综合分析和判断。本文首先介绍了多模态深度学习的基本概念和工作原理,对深度学习技术应用于多模态医学影像辅助诊断的代表性研究成果做出综述,分析了多模态深度学习在医学影像领域的技术挑战,并对该技术的应用前景作出展望。

     

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  • 收稿日期:  2022-02-24
  • 网络出版日期:  2022-06-21
  • 刊出日期:  2022-05-20

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