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相关实验视频

Updated: Sep 16, 2025

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation
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人工智能系统用于EUS导航和解剖学地标识别.

Gianenrico Rizzatti1, Giulia Tripodi1, Sara Sofia De Lucia1

  • 1Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.

VideoGIE : an official video journal of the American Society for Gastrointestinal Endoscopy
|July 11, 2025
PubMed
概括

人工智能 (AI) 系统现在可以在内镜超声波 (EUS) 检查期间识别解剖学地标. 这种深度学习技术有望改善EUS培训和质量控制.

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科学领域:

  • 医学技术 医学技术 医学技术
  • 医学中的人工智能
  • 内镜超声波 (EUS) 的使用

背景情况:

  • 人工智能 (AI) 在包括内镜在内的各种医疗领域显示出潜力.
  • 人工智能在EUS中的应用正在出现,最初的研究重点是胰腺质量识别.
  • 最近的进展包括设计用于实时解剖学里程碑识别的AI系统在诊断EUS期间.

研究的目的:

  • 评估人工智能系统,在诊断EUS期间实时识别解剖学里程碑.
  • 评估系统在EUS程序中识别关键解剖结构的准确性.

主要方法:

  • 使用了Endoangel系统,利用深层卷积神经网络 (DCNNs).
  • 该DCNN接受了超过550个EUS程序的训练,用于特征提取和预测.
  • 该系统在接受诊断EUS的三名患者中进行了测试.

主要成果:

  • 在测试过程中,AI EUS系统成功地在实时中识别了解剖学里程碑.
  • 执行EUS的专家评估了地标识别的准确性.
  • 该系统没有识别胰腺质量或囊性病变等病理发现.

结论:

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  • 基于DCNN的AI EUS系统准确地识别了解剖学地标.
  • 这项技术在EUS培训和质量保证方面具有潜在的应用.
  • 未来的发展可能包括对病理变化的鉴定.