Three-dimensional scanners have been widely applied in image-guided surgery (IGS) given its potential to solve the image-to-patient registration problem. How to perform a reliable calibration between a 3D scanner and an external tracker is especially important for these applications. This study proposes a novel method for calibrating the extrinsic parameters of a 3D scanner in the coordinate system of an optical tracker. We bound an optical marker to a 3D scanner and designed a specified 3D benchmark for calibration. We then proposed a two-step calibration method based on the pointset registration technique and nonlinear optimization algorithm to obtain the extrinsic matrix of the 3D scanner. We applied repeat scan registration error (RSRE) as the cost function in the optimization process. Subsequently, we evaluated the performance of the proposed method on a recaptured verification dataset through RSRE and Chamfer distance (CD). In comparison with the calibration method based on 2D checkerboard, the proposed method achieved a lower RSRE (1.73 mm vs. 2.10, 1.94, and 1.83 mm) and CD (2.83mm vs. 3.98, 3.46, and 3.17mm). We also constructed a surgical navigation system to further explore the application of the tracked 3D scanner in image-to-patient registration. We conducted a phantom study to verify the accuracy of the proposed method and analyze the relationship between the calibration accuracy and the target registration error (TRE). The proposed scanner-based image-to-patient registration method was also compared with the fiducial-based method, and TRE and operation time (OT) were used to evaluate the registration results. The proposed registration method achieved an improved registration efficiency (50.72±6.04 s vs. 212.97±15.91 s in the head phantom study). Although the TRE of the proposed registration method met the clinical requirements, its accuracy was lower than that of the fiducial-based registration method (1.79±0.17 mm vs. 0.92±0.16 mm in the head phantom study). We summarized and analyzed the limitations of the scanner-based image-to-patient registration method and discussed its possible development.

中文翻译：

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在光学跟踪器的坐标系统中校准3D扫描仪以进行图像到患者的配准

三维扫描仪已被广泛应用于图像引导手术（IGS）中，因为它具有解决图像对患者配准问题的潜力。对于这些应用，如何在3D扫描仪和外部跟踪器之间执行可靠的校准尤为重要。这项研究提出了一种用于校准光学跟踪器坐标系中3D扫描仪外部参数的新颖方法。我们将光学标记器绑定到3D扫描仪，并设计了一个指定的3D基准进行校准。然后，我们提出了一种基于点集配准技术和非线性优化算法的两步校准方法，以获取3D扫描仪的外在矩阵。在优化过程中，我们将重复扫描配准误差（RSRE）用作成本函数。随后，我们通过RSRE和倒角距离（CD）在重新捕获的验证数据集上评估了该方法的性能。与基于2D棋盘格的校准方法相比，所提出的方法获得了更低的RSRE（1.73毫米对2.10、1.94和1.83毫米）和CD（2.83毫米对3.98、3.46和3.17毫米）。我们还构建了外科手术导航系统，以进一步探索跟踪的3D扫描仪在图像到患者登记中的应用。我们进行了幻像研究，以验证所提出方法的准确性，并分析校准准确性与目标配准误差（TRE）之间的关系。还将提出的基于扫描仪的图像对患者的注册方法与基于基准的方法进行比较，并使用TRE和手术时间（OT）来评估注册结果。所提出的配准方法实现了提高的配准效率（50.72±6.04 s与头模研究中的212.97±15.91 s）。尽管所提出的配准方法的TRE符合临床要求，但其准确性低于基于基准的配准方法（1.79±0.17 mm对头部幻像研究的0.92±0.16 mm）。我们总结并分析了基于扫描仪的图像对患者配准方法的局限性，并讨论了其可能的发展。