School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.
Int J Med Robot. 2019 Aug;15(4):e2008. doi: 10.1002/rcs.2008. Epub 2019 Jun 14.
To improve the positioning accuracy of tunnels for anterior cruciate ligament (ACL) reconstruction, we proposed an intensity-based 2D-3D registration method for an ACL reconstruction navigation system. Methods for digitally reconstructed radiograph (DRR) generation, similarity measurement, and optimization are crucial to 2D-3D registration. We evaluated the accuracy, success rate, and processing time of different methods: (a) ray-casting and splating were compared for DRR generation; (b) normalized mutual information (NMI), Mattes mutual information (MMI), and Spearman's rank correlation coefficient (SRC) were assessed for similarity between registrations; and (c) gradient descent (GD) and downhill simplex (DS) were compared for optimization. The combination of splating, SRC, and GD provided the best composite performance and was applied in an augmented reality (AR) ACL reconstruction navigation system. The accuracy of the navigation system could fulfill the clinical needs of ACL reconstruction, with an end pose error of 2.50 mm and an angle error of 2.74°.
为了提高前交叉韧带 (ACL) 重建隧道的定位精度,我们提出了一种基于强度的 ACL 重建导航系统的 2D-3D 配准方法。数字重建射线照片 (DRR) 生成、相似性测量和优化方法对于 2D-3D 配准至关重要。我们评估了不同方法的准确性、成功率和处理时间:(a) 比较了光线投射和表面绘制法进行 DRR 生成;(b) 评估了配准之间的相似性的归一化互信息 (NMI)、Mattes 互信息 (MMI) 和 Spearman 秩相关系数 (SRC);(c) 比较了梯度下降 (GD) 和下山单纯形 (DS) 进行优化。表面绘制、SRC 和 GD 的组合提供了最佳的综合性能,并应用于增强现实 (AR) ACL 重建导航系统中。导航系统的准确性可以满足 ACL 重建的临床需求,末端姿势误差为 2.50mm,角度误差为 2.74°。