the Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
the Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Comput Methods Programs Biomed. 2024 Dec;257:108444. doi: 10.1016/j.cmpb.2024.108444. Epub 2024 Oct 9.
Image-based 2D/3D registration is a crucial technology for fluoroscopy-guided surgical interventions. However, traditional registration methods relying on a single X-ray image into surgical navigation systems. This study proposes a novel 2D/3D registration approach utilizing biplanar X-ray images combined with computed tomography (CT) to significantly reduce registration and navigation errors. The method is successfully implemented in a surgical navigation system, enhancing its precision and reliability.
First, we simultaneously register the frontal and lateral X-ray images with the CT image, enabling mutual complementation and more precise localization. Additionally, we introduce a novel similarity measure for image comparison, providing a more robust cost function for the optimization algorithm. Furthermore, a multi-resolution strategy is employed to enhance registration efficiency. Lastly, we propose a more accurate coordinate transformation method, based on projection and 3D reconstruction, to improve the precision of surgical navigation systems.
We conducted registration and navigation experiments using pelvic, spinal, and femur phantoms. The navigation results demonstrated that the feature registration errors (FREs) in the three experiments were 0.505±0.063 mm, 0.515±0.055 mm, and 0.577±0.056 mm, respectively. Compared to the point-to-point (PTP) registration method based on anatomical landmarks, our method reduced registration errors by 31.3%, 23.9%, and 26.3%, respectively.
The results demonstrate that our method significantly reduces registration and navigation errors, highlighting its potential for application across various anatomical sites. Our code is available at: https://github.com/SJTUdemon/2D-3D-Registration.
基于图像的 2D/3D 配准是透视引导手术干预的关键技术。然而，传统的配准方法依赖于单一的 X 射线图像进入手术导航系统。本研究提出了一种新的 2D/3D 配准方法，利用双平面 X 射线图像与计算机断层扫描（CT）相结合，显著降低配准和导航误差。该方法已成功应用于手术导航系统，提高了其精度和可靠性。
首先，我们同时将正面和侧面 X 射线图像与 CT 图像进行配准，实现相互补充和更精确的定位。此外，我们引入了一种新的图像比较相似性度量方法，为优化算法提供了更健壮的代价函数。此外，还采用多分辨率策略来提高配准效率。最后，我们提出了一种更准确的坐标变换方法，基于投影和 3D 重建，以提高手术导航系统的精度。
我们使用骨盆、脊柱和股骨模型进行了配准和导航实验。导航结果表明，三个实验的特征配准误差（FRE）分别为 0.505±0.063mm、0.515±0.055mm 和 0.577±0.056mm。与基于解剖标志点的点对点（PTP）配准方法相比，我们的方法分别减少了 31.3%、23.9%和 26.3%的配准误差。
结果表明，我们的方法显著降低了配准和导航误差，突显了其在各种解剖部位应用的潜力。我们的代码可在以下网址获得：https://github.com/SJTUdemon/2D-3D-Registration。
