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基于机器人的程序用于腹部器官的3D重建,使用代式最接近点和姿势图算法.

Birthe Göbel1,2, Jonas Huurdeman2,3, Alexander Reiterer1,4

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科学领域:

  • 医疗机器人 医疗机器人
  • 手术导航 手术导航
  • 计算机视觉 计算机视觉

背景情况:

  • 机器人辅助手术和图像引导导航正在推动腹腔镜的发展.
  • 摄像机和机器人之间的精确转换数据对于图像采集至关重要.
  • 传统的手眼校准是复杂的,每次手术后都需要进行,这对临床环境构成了挑战.

研究的目的:

  • 开发基于机器人的多视图3D重建程序,绕过手动手眼校准的需要.
  • 实现姿势优化算法,以确定相机机器人转换.
  • 为了实现有效和准确的3D重建,用于最少的侵入性手术.

主要方法:

  • 使用机器人手臂和立体腹腔镜进行图像采集.
  • 使用半全球匹配 (OpenCV) 用于立体声深度测量.
  • 应用多尺度颜色代最接近点和多路注册与姿势图 (Open3D) 姿势优化.

主要成果:

  • 实现了低根平均平方误差 (1.1-3.37毫米).
  • 为详细的3D模型生成密集的点云.
  • 在不需要手眼校准的情况下展示了可信的3D重建.

结论:

  • 拟议的方法为机器人辅助腹腔镜中复杂的手眼校准提供了可行的替代方案.
  • 姿势优化有效地弥补了手动校准的缺乏.
  • 这种方法促进了高效的3D重建,以改善外科指导.