Cortical surface registration for image-guided neurosurgery using laser-range scanning
Cortical surface registration for image-guided neurosurgery using laser-range scanning
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DOI：
10.1109/tmi.2003.815868
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发表时间：
2003-08-01
影响因子：
10.6
通讯作者：
Weil, RJ
中科院分区：
文献类型：
--
作者：
Miga, MI;Sinha, TK;Weil, RJ
在本文中，提出了一种使用激光距离扫描仪(LRS)获取术中数据的方法，该方法是在模型更新的图像引导手术的背景下进行的。利用已建立的基于点和表面的技术以及通过互信息结合几何和强度信息(SurfaceMI)的新方法，探索将LRS生成的纹理点云配准到层析数据。进行了幻影配准研究，以检查每个框架的准确性和稳健性。此外，还进行了活体配准，以验证数据采集系统在手术室中的可行性。结果表明，对于纹理点云的配准，SurfaceMI在很多情况下都优于基于点的(PBR)和迭代最近点(ICP)方法。体模中模拟深层组织靶点的平均靶点配准误差(TRE)分别为1.0+/-0.2 mm、2.0+/-0.3 mm和1.2+/-0.3 mm。在体内注册方面，PBR、ICP和SurfaceMI每个支架的血管轮廓点的平均TRE分别为1.9+/-1.0、0.9+/-0.6和1.3+/-0.5。本文讨论的方法与量化数据相结合，为在模型更新的图像引导手术框架内使用LRS技术提供了动力。
In this paper, a method of acquiring intraoperative data using a laser range scanner (LRS) is presented within the context of model-updated image-guided surgery. Registering textured point clouds generated by the LRS to tomographic data is explored using established point-based and surface techniques as well as a novel method that incorporates geometry and intensity information via mutual information (SurfaceMI). Phantom registration studies were performed to examine accuracy and robustness for each framework. In addition, an in vivo registration is performed to demonstrate feasibility of the data acquisition system in the operating room. Results indicate that SurfaceMI performed better in many cases than point-based (PBR) and iterative closest point (ICP) methods for registration of textured point clouds. Mean target registration error (TRE) for simulated deep tissue targets in a phantom were 1.0 +/- 0.2, 2.0 +/- 0.3, and 1.2 +/- 0.3 mm for PBR, ICP, and SurfaceMI, respectively. With regard to in vivo registration, the mean TRE of vessel contour points for each framework was 1.9 +/- 1.0, 0.9 +/- 0.6, and 1.3 +/- 0.5 for PBR, ICP, and SurfaceMI, respectively. The methods discussed in this paper in conjunction with the quantitative data provide impetus for using LRS technology within the model-updated image-guided surgery framework.