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肝癌的医学影像智能化诊断研究进展

徐捷 徐文斌 贺柯庆 上官定 徐婷 谢明君 龙年宝 葛来安

引用本文:
Citation:

肝癌的医学影像智能化诊断研究进展

DOI: 10.12449/JCH240925
基金项目: 

江西省中医药管理局科技项目 (2021B695)

利益冲突声明:本文不存在任何利益冲突。
作者贡献声明:徐捷负责初稿撰写、论文资料收集与总结;徐文斌参与初稿撰写、资料收集、论文审阅与修订;贺柯庆、谢明君参与论文资料整理;上官定、徐婷、龙年宝参与论文资料收集;葛来安负责论文审阅与修订。
详细信息
    通信作者:

    葛来安, 13970998757@163.com (ORCID: 0009-0007-4544-1706)

Research advances in the intelligent medical imaging diagnosis of liver cancer

Research funding: 

The Science and Technology Project of Jiangxi Provincial Administration of Traditional Chinese Medicine (2021B695)

More Information
  • 摘要: 肝癌是对人体威胁最大的疾病之一,大部分患者确诊时已属晚期,致死率极高。早期肝癌的诊断和治疗是改善患者预后的关键。医学影像是辅助诊断肝癌的重要手段,当前基于医学影像数据的智能图像识别技术已深入涉足医学诊断领域并具有良好应用前景。本文通过综述目前人工智能方法在肝脏医学影像中诊断局灶性肝脏病变的研究现状,提出当前人工智能诊断的优势与不足,旨在为今后肝癌的智能化诊断提供新的研究思路。

     

  • 图  1  U-Net模型框架结构

    Figure  1.  U-Net model framework structure

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    中华医学会放射学分会医学影像大数据与人工智能工作委员会, 中华医学会放射学分会腹部学组, 中华医学会放射学分会磁共振学组. 肝脏局灶性病变CT和MRI标注专家共识(2020)[J]. 中华放射学杂志, 2020, 54( 12): 1145- 1152. DOI: 10.3760/cma.j.cn112149-20200706-00893.
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  • 收稿日期:  2023-12-10
  • 录用日期:  2024-02-18
  • 出版日期:  2024-09-25
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