NeuroLens:在外科培训中使用自然语言命令进行器官定位,以进行解剖学识别
Nevin M Matasyoh1, Daniel Delev2, Waseem Masalha2
1Surgical Planning and Robotic Cognition Laboratory (SPARC), Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-Nuremberg, Nürnberger Str. 74, 91052, Erlangen, Bavaria, Germany.
概括
多式联络系统NeuroLens使用视频和文字准确识别解剖结构,用于外科训练. 它显示了高的可用性和性能,增强了学员的解剖学学习.
科学领域:
- 神经外科 神经外科
- 医学教育 医学教育
- 计算机视觉 计算机视觉
背景情况:
- 传统的外科培训依赖于尸体和2D地图,限制了实时解剖视觉化.
- 需要交互式数字工具来提高解剖学识别和手术技能的获得.
研究的目的:
- 介绍NeuroLens,一个多式系统,用于增强神经外科手术中的解剖识别.
- 为外科实习生开发一个交互式学习平台,使用集成的视频,文本和语音输入.
主要方法:
- 在神经内镜视频上训练了一种多式深度学习本地化模型.
- 该系统处理带有文字/语音描述的视频,以识别和定位解剖结构.
- 可用性通过系统可用性量表 (SUS) 和来自五名参与者的用户反来评估.
主要成果:
- NeuroLens实现了100%的预测类准确性和79.69%的定位准确性.
- 该系统表现出强大的可用性,平均SUS得分为71.5.5.
- 用户发现设计直观和响应,建议3D可视化增强.
结论:
- NeuroLens有效地整合了多模式输入,用于准确的解剖检测和定位.
- 该系统提供了一个有价值的,可用的工具,用于改善外科手术培训中的解剖学学习.
- 未来的工作包括更大的评估和整合3D可视化以提高效率.
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