通过结石和外科工具细分来改善基于SLAM的灵活尿道镜导航
Laura Oliva-Maza1,2, Florian Steidle1, Julian Klodmann1
1Institute of Robotics and Mechatronics German Aerospace Center (DLR) Wessling Germany.
Healthcare technology letters
|December 11, 2025
概括
这项研究通过提高视觉SLAM准确度来增强灵活的尿路透镜导航. 通过细分结石和手术工具,它可以提高尿管镜位置估计,以便更好地去除石头.
科学领域:
- 医疗工程 医学工程
- 计算机视觉 计算机视觉
- 手术导航 手术导航
背景情况:
- 灵活的尿路透镜是治疗结石的关键.
- 精确的尿道镜跟踪对于完整的石头提取至关重要.
- 现有的视觉SLAM系统与动态的外科环境作斗争.
研究的目的:
- 为了提高视觉SLAM的稳定性和准确性,用于灵活的尿路透镜.
- 调整SLAM算法以适应动态的手术内条件,包括移动的石头和仪器.
- 将实时对象细分集成到外科导航系统中.
主要方法:
- 使用YOLOv7-E6E与Segment Anything (SAM) 和YOLO11m-seg进行结石和手术工具的实时细分.
- 修改了SLAM框架,将手术仪器视为被丢弃的动态元素.
- 将结石像素归类为潜在的动态地图点,允许它们在SLAM框架内消失.
- 使用记录的数据集进行细分和尿管镜位估计来评估方法.
主要成果:
- 通过使用YOLOv7-E6E与SAM,在尿管镜中估计了35.4%的平均改善.
- 在使用YOLO11m-seg.的尿管镜姿势估计表现出了52.49%的显著平均改善.
- 精细的SLAM方法在动态手术场景中显示出更高的准确性和稳定性.
结论:
- 动态元素的实时细分显著改善了灵活尿路透镜中的视觉SLAM性能.
- 拟议的方法提高了尿路望远镜导航的准确性,这对于彻底去除结石至关重要.
- 这一进步为执行尿路透镜手术的外科医生提供了更可靠的导航工具.
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