Intraoperative image-based multiview 2D/3D registration for image-guided orthopaedic surgery: incorporation of fiducial-based C-arm tracking and GPU-acceleration.
Intraoperative image-based multiview 2D/3D registration for image-guided orthopaedic surgery: incorporation of fiducial-based C-arm tracking and GPU-acceleration.
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DOI：
10.1109/tmi.2011.2176555
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发表时间：
2012-04
影响因子：
10.6
通讯作者：
Taylor RH
中科院分区：
文献类型：
--
作者：
Otake Y;Armand M;Armiger RS;Kutzer MD;Basafa E;Kazanzides P;Taylor RH
术中患者配准可能会显着影响图像引导手术（IGS）的结果。与目前占主导地位的基于点的直接接触方法相比，基于图像的配准方法具有多种优势，并用于固定 X 射线机架的图像引导放射治疗的一些行业解决方案中。然而，包括几何校准和计算成本在内的技术挑战阻碍了它们与 IGS 移动 C 形臂的使用。我们提出了一种用于术中患者配准的 2D/3D 配准框架，使用传统的移动 X 射线成像仪结合基于基准的 C 形臂跟踪和图形处理单元 (GPU) 加速。两阶段框架 1) 获取 X 射线图像并使用定制的图像内基准估计图像之间的相对姿势，2) 使用基于强度的 2D/3D 配准估计患者姿势。已经使用公开的金标准数据集、塑料骨模型和尸体标本进行了实验验证。两幅图像相距 90° 的体模的平均目标配准误差 (mTRE) 为 0.34 ± 0.04 mm（成功率：100%，配准时间：14.2 s），图像相距 58.5° 的尸体标本的平均目标配准误差（mTRE）为 0.99 ± 0.41 mm（81%，16.3 s）。实验结果表明所提出的注册框架作为 IGS 例程的实用替代方案的可行性。
Intraoperative patient registration may significantly affect the outcome of image-guided surgery (IGS). Image-based registration approaches have several advantages over the currently dominant point-based direct contact methods and are used in some industry solutions in image-guided radiation therapy with fixed X-ray gantries. However, technical challenges including geometric calibration and computational cost have precluded their use with mobile C-arms for IGS. We propose a 2D/3D registration framework for intraoperative patient registration using a conventional mobile X-ray imager combining fiducial-based C-arm tracking and graphics processing unit (GPU)-acceleration. The two-stage framework 1) acquires X-ray images and estimates relative pose between the images using a custom-made in-image fiducial, and 2) estimates the patient pose using intensity-based 2D/3D registration. Experimental validations using a publicly available gold standard dataset, a plastic bone phantom and cadaveric specimens have been conducted. The mean target registration error (mTRE) was 0.34 ± 0.04 mm (success rate: 100%, registration time: 14.2 s) for the phantom with two images 90° apart, and 0.99 ± 0.41 mm (81%, 16.3 s) for the cadaveric specimen with images 58.5° apart. The experimental results showed the feasibility of the proposed registration framework as a practical alternative for IGS routines.