PURPOSE The surface-based registration approach to laparoscopic augmented reality (AR) has clear advantages. Nonrigid point-set registration paves the way for surface-based registration. Among current non-rigid point set registration methods, the coherent point drift (CPD) algorithm is rarely used because of two challenges: (1) volumetric deformation is difficult to predict, and (2) registration from intraoperative visible tissue surface to whole anatomical preoperative model is a "part-to-whole" registration that CPD cannot be applied directly to. We preliminarily applied CPD on surgical navigation for laparoscopic partial nephrectomy (LPN). However, it introduces normalization errors and lacks navigation robustness. This paper presents important advances for more effectively applying CPD to LPN surgical navigation while attempting to quantitatively evaluate the accuracy of CPD-based surgical navigation. METHODS First, an optimized volumetric deformation (Op-VD) algorithm is proposed to achieve accurate prediction of volume deformation. Then, a projection-based partial selection method is presented to conveniently and robustly apply the CPD to LPN surgical navigation. Finally, kidneys with different deformations in vitro, phantom and in vivo experiments are performed to evaluate the accuracy and effectiveness of our approach. RESULTS The average root-mean-square error of volume deformation was refined to 0.84 mm. The mean target registration error (TRE) of the surface and inside markers in the in vitro experiments decreased to 1.51 mm and 1.29 mm, respectively. The robustness and precision of CPD-based navigation were validated in phantom and in vivo experiments, and the mean navigation TRE of the phantom experiments was found to be [Formula: see text] mm. CONCLUSION Accurate volumetric deformation and robust navigation results can be achieved in AR navigation of LPN by using surface-based registration with CPD. Evaluation results demonstrate the effectiveness of our proposed methods while showing the clinical application potential of CPD. This work has important guiding significance for the application of the CPD in laparoscopic AR.

中文翻译：

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相干点漂移算法在腹腔镜部分肾切除术增强现实手术导航中的评估和应用。

目的腹腔镜增强现实（AR）的基于表面的配准方法具有明显的优势。非刚性点集套准为基于曲面的套准铺平了道路。在当前的非刚性点集配准方法中，由于两个挑战，很少使用相干点漂移（CPD）算法：（1）难以预测体积变形；（2）从术中可见组织表面到整个解剖术前的配准模型是CPD不能直接应用到的“整体”注册。我们初步将CPD应用于腹腔镜部分肾切除术（LPN）的手术导航。但是，它引入了归一化错误，并且缺乏导航鲁棒性。本文提出了重要的进展，旨在更有效地将CPD应用于LPN手术导航，同时尝试定量评估基于CPD的手术导航的准确性。方法首先，提出一种优化的体积变形（Op-VD）算法，以实现对体积变形的准确预测。然后，提出了一种基于投影的局部选择方法，以方便，可靠地将CPD应用于LPN手术导航。最后，进行了体外，体模和体内实验中具有不同变形的肾脏，以评估我们方法的准确性和有效性。结果体积变形的平均均方根误差精确到0.84 mm。在体外实验中，表面和内部标记的平均目标配准误差（TRE）降低至1.51 mm和1.29 mm，分别。在幻影和体内实验中验证了基于CPD导航的鲁棒性和精确度，并且幻影实验的平均导航TRE为[公式：参见文本] mm。结论在LPN的AR导航中，通过使用基于表面的CPD配准可以实现准确的体积变形和鲁棒的导航结果。评估结果证明了我们提出的方法的有效性，同时显示了CPD的临床应用潜力。这项工作对于CPD在腹腔镜AR中的应用具有重要的指导意义。结论在LPN的AR导航中，使用基于表面的CPD配准可以实现准确的体积变形和鲁棒的导航结果。评估结果证明了我们提出的方法的有效性，同时显示了CPD的临床应用潜力。这项工作对于CPD在腹腔镜AR中的应用具有重要的指导意义。结论在LPN的AR导航中，通过使用基于表面的CPD配准可以实现准确的体积变形和鲁棒的导航结果。评估结果证明了我们提出的方法的有效性，同时显示了CPD的临床应用潜力。这项工作对于CPD在腹腔镜AR中的应用具有重要的指导意义。