基于CAD模型的双C臂图像中椎弓根螺钉配对与配准用于螺钉位姿估计
Pedicle Screw Pairing and Registration for Screw Pose Estimation from Dual C-arm Images Using CAD Models
AI总结：
本文提出利用螺钉CAD三维模型进行2D-3D对齐，从双C臂图像中实现椎弓根螺钉配对与位姿估计，实验表明正确螺钉组合在所有测试中均优于错误配对，并能显著降低投影误差。
摘要：
在前后位（AP）和侧位（LAT）图像中准确匹配椎弓根螺钉对于脊柱减压和稳定手术的成功至关重要。然而，建立螺钉对应关系，尤其是在侧位视图中，仍然是一个重大的临床挑战。本文提出了一种从双C臂图像中解决椎弓根螺钉对应关系和位姿估计问题的方法。通过比较螺钉组合，该方法在配对和配准任务中均表现出一致的准确性。该方法还利用螺钉CAD三维模型进行2D-3D对齐，以从双视图准确配对并估计螺钉位姿。我们的结果表明，在所有测试用例中，正确的螺钉组合始终优于错误配对，甚至在配准之前也是如此。配准之后，正确的组合进一步增强了投影与图像之间的对齐，显著降低了投影误差。该方法通过提供可靠的螺钉定位反馈，有望改善脊柱手术的手术效果。
英文摘要：
Accurate matching of pedicle screws in both anteroposterior (AP) and lateral (LAT) images is critical for successful spinal decompression and stabilization during surgery. However, establishing screw correspondence, especially in LAT views, remains a significant clinical challenge. This paper introduces a method to address pedicle screw correspondence and pose estimation from dual C-arm images. By comparing screw combinations, the approach demonstrates consistent accuracy in both pairing and registration tasks. The method also employs 2D-3D alignment with screw CAD 3D models to accurately pair and estimate screw pose from dual views. Our results show that the correct screw combination consistently outperforms incorrect pairings across all test cases, even prior to registration. After registration, the correct combination further enhances alignment between projections and images, significantly reducing projection error. This approach shows promise for improving surgical outcomes in spinal procedures by providing reliable feedback on screw positioning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
