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根据iOCT指导,实时变形感知控制用于自主机器人上网膜注射.

Demir Arikan1,2, Peiyao Zhang2, Michael Sommersperger1

  • 1Department of Computer Science, Technische Universitat München, Munich 85748 Germany.

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|September 12, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新方法,用于使用手术内光学相干断层扫描 (iOCT) 进行机器人脑下注射. 该技术通过考虑组织变形来提高针的准确性,在产生子内血栓方面达到90%的成功率.

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科学领域:

  • 眼科医生 眼科 眼科
  • 机器人技术 机器人技术 机器人技术
  • 医疗成像医学成像

背景情况:

  • 机器人平台提高了视网膜微手术的精度.
  • 内手术光学连贯性断层扫描 (iOCT) 能够通过图像引导的机器人干预,用于自主治疗,如子注射.
  • 工具与组织相互作用期间的组织变形对自主IOCT引导的机器人内注射构成了挑战,影响了针头的定位和结果.

研究的目的:

  • 根据IOCT指南,提出一种针对组织变形的自主下注射的新方法.
  • 为了提高机器人脑下注射的准确性和可靠性.

主要方法:

  • 从密集采样的iOCT B扫描 (B5扫描) 进行手术场景的实时细分和3D重建.
  • 监测仪器相对于虚拟目标层的位置 (在内界膜和视网膜颜料上皮之间).
  • 基于实时数据的针头插入深度的动态调整.

主要成果:

  • 这种新方法证明了插入深度的动态调整.
  • 与以前的自主方法相比,针头定位的准确性大大提高.
  • 在90%的实验中可靠地创建了下膜,这与之前的方法的35%成功率相比大幅增加.

结论:

  • 拟议的技术有效地管理在自主IOCT引导的机器人内注射过程中组织变形.
  • 这种方法为内注射程序提供了更准确,更可靠的方法.
  • 该研究提供了公开可用的源代码和数据,用于进一步的研究和开发.