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An Efficient Method for Estimating Soft Tissue Deformation Based on Intraoperative Stereo Image Features and Point-Based Registration

机译:基于术中立体图像特征和基于点的配准的软组织变形估计方法

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摘要

Estimation of soft tissue deformation occurring during image-guided surgery using an easily implemented and accurate method is necessary. Using a stereo camera, this study focuses on two efficient methods for estimating soft tissue deformation. Two methods were proposed to overcome limitations associated with the typical methods used for estimating soft tissue deformation, such as dependence on accuracy of the operator and indentation of skin. The first method is based on Triclops SDK, and the second method is based on projecting a pattern to acquire P-Lands (Projected Landmarks). Based on the proposed methods, surface information is acquired in the form of point clouds of surface point coordinates to the submillimeter accuracy. The reconstructed predeformation three-dimensional (3D) point cloud obtained for each method is registered with a modified iterative closest point algorithm to a postdeformation 3D point cloud obtained from the same region of interest. Results were compared with an MRI-MRI registration method as a control. Results are provided as RMS differences between the initial and final coordinates of corresponding points. The average RMS difference for the typical method is 3.53 mm, that for the Triclops SDK method is 2.32 mm, and that for the P-Lands projection method is 2.06 mm. The MRI-MRI registration had an average RMS difference of 1.12 mm. Using MRI-MRI registration as the gold standard, the average error obtained for the typical method was 2.41 mm, that for the first method was 1.2 mm, and that for the second method was 0.94 mm.
机译:必须使用一种易于实施且准确的方法来估计在图像引导手术期间发生的软组织变形。本研究使用立体相机,着重于估计软组织变形的两种有效方法。提出了两种方法来克服与用于估计软组织变形的典型方法相关的局限性,例如对操作者准确性和皮肤压痕的依赖性。第一种方法基于Triclops SDK,第二种方法基于投影模式以获取P-Lands(投影地标)。基于所提出的方法,以表面点坐标的点云的形式获取表面信息,以达到亚毫米精度。为每种方法获得的重构的变形前三维(3D)点云都使用改进的迭代最近点算法进行配准,该算法与从相同关注区域获得的变形后3D点云相对应。将结果与MRI-MRI配准方法进行比较。结果以对应点的初始坐标和最终坐标之间的RMS差的形式提供。典型方法的平均RMS差为3.53 mm,Triclops SDK方法的平均RMS差为2.32 mm,P土地投影方法的平均RMS差为2.06 mm。 MRI-MRI配准的平均RMS差为1.12 mm。使用MRI-MRI配准作为金标准,典型方法的平均误差为2.41 mm,第一种方法的平均误差为1.2 mm,第二种方法的平均误差为0.94 mm。

著录项

  • 来源
  • 作者单位

    Department of Medical Physics and Biomedical Engineering, Image Guided Intervention Group,Research Centre for Biomedical Technology & Robotics, RCBTR, Tehran University of Medical Sciences, Tehran, Iran;

    Department of Medical Physics and Biomedical Engineering, Image Guided Intervention Group,Research Centre for Biomedical Technology & Robotics, RCBTR, Tehran University of Medical Sciences, Tehran, Iran;

    Department of Medical Physics and Biomedical Engineering, Image Guided Intervention Group,Research Centre for Biomedical Technology & Robotics, RCBTR, Tehran University of Medical Sciences, Tehran, Iran;

    Department of Medical Physics and Biomedical Engineering, Image Guided Intervention Group,Research Centre for Biomedical Technology & Robotics, RCBTR, Tehran University of Medical Sciences, Tehran, Iran;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    soft tissue; deformation estimation; intraoperative stereo images; projected landmarks; point-based registration;

    机译:软组织;变形估计术中立体影像;投影地标;基于点的注册;
  • 入库时间 2022-08-17 13:36:48

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