Billings Seth, Kang Hyun Jae, Cheng Alexis, Boctor Emad, Kazanzides Peter, Taylor Russell
Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA,
Int J Comput Assist Radiol Surg. 2015 Jun;10(6):761-71. doi: 10.1007/s11548-015-1188-z. Epub 2015 Apr 18.
We present a registration method for computer-assisted total hip replacement (THR) surgery, which we demonstrate to improve the state of the art by both reducing the invasiveness of current methods and increasing registration accuracy. A critical element of computer-guided procedures is the determination of the spatial correspondence between the patient and a computational model of patient anatomy. The current method for establishing this correspondence in robot-assisted THR is to register points intraoperatively sampled by a tracked pointer from the exposed proximal femur and, via auxiliary incisions, from the distal femur.
In this paper, we demonstrate a noninvasive technique for sampling points on the distal femur using tracked B-mode ultrasound imaging and present a new algorithm for registering these data called Projected Iterative Most-Likely Oriented Point (P-IMLOP). Points and normal orientations of the distal bone surface are segmented from ultrasound images and registered to the patient model along with points sampled from the exposed proximal femur via a tracked pointer.
The proposed approach is evaluated using a bone- and tissue-mimicking leg phantom constructed to enable accurate assessment of experimental registration accuracy with respect to a CT-image-based model of the phantom. These experiments demonstrate that localization of the femur shaft is greatly improved by tracked ultrasound. The experiments further demonstrate that, for ultrasound-based data, the P-IMLOP algorithm significantly improves registration accuracy compared to the standard ICP algorithm.
Registration via tracked ultrasound and the P-IMLOP algorithm has high potential to reduce the invasiveness and improve the registration accuracy of computer-assisted orthopedic procedures.
我们提出一种用于计算机辅助全髋关节置换(THR)手术的配准方法,通过降低现有方法的侵入性并提高配准精度,证明该方法改进了现有技术水平。计算机引导手术的一个关键要素是确定患者与患者解剖结构计算模型之间的空间对应关系。在机器人辅助THR中建立这种对应关系的当前方法是在术中通过跟踪指针从暴露的股骨近端以及通过辅助切口从股骨远端采集点。
在本文中,我们展示了一种使用跟踪B型超声成像在股骨远端采集点的非侵入性技术,并提出了一种用于配准这些数据的新算法,称为投影迭代最可能定向点(P - IMLOP)。从超声图像中分割出远端骨表面的点和法向方向,并与通过跟踪指针从暴露的股骨近端采集的点一起配准到患者模型。
使用构建的骨和组织模拟腿部模型对所提出的方法进行评估,该模型能够相对于基于CT图像的模型准确评估实验配准精度。这些实验表明,跟踪超声极大地提高了股骨干的定位。实验进一步表明,对于基于超声的数据,与标准ICP算法相比,P - IMLOP算法显著提高了配准精度。
通过跟踪超声和P - IMLOP算法进行配准具有很大潜力,可以降低侵入性并提高计算机辅助骨科手术的配准精度。