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Toward an End-to-End Calibration for Mobile C-Arm in Combination with a Depth Sensor for Surgical Augmented Reality Applications

机译:结合外科手术增强现实应用的深度传感器实现移动C型臂的端到端校准

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摘要

C-arm X-ray imaging is commonly applied in operating rooms for guiding orthopedic surgeries. Augmented Reality (AR) with C-arm X-ray images during surgery is an efficient way to facilitate procedures for surgeons. However, the accurate calibration process for surgical AR based on C-arm is essential and still challenging due to the limitations of C-arm imaging systems, such as instability of C-arm calibration parameters and the narrow field of view. We extend existing methods using a depth camera and propose a new calibration procedure consisting of calibration of the C-arm imaging system, and 3D/2D calibration of an RGB-D camera and C-arm system with a new method to achieve reliable data and promising accuracy and, at the same time, consistent with standard surgical protocols. For the calibration procedure, we apply bundle adjustment equations with a 3D designed Lego multi-modal phantom, in contrast to the previous methods in which planar calibration phantoms were applied. By using our method, the visualization of the X-ray image upon the 3D data was done, and the achieved mean overlay error was 1.03 mm. The evaluations showed that the proposed calibration procedure provided promising accuracy for AR surgeries and it improved the flexibility and robustness of existing C-arm calibration methods for surgical augmented reality (using C-arm and RGB-D sensor). Moreover, the results showed the efficiency of our method to compensate for the effects of the C-arm movement on calibration parameters. It was shown that the obtained overlay error was improved for the non-zero rotation movement of C-arm by using a virtual detector.
机译:C臂X射线成像通常用于手术室,以指导骨科手术。手术过程中带有C型臂X射线图像的增强现实(AR)是简化外科医生程序的有效方法。然而,由于C臂成像系统的局限性,例如C臂校准参数的不稳定性和狭窄的视野,基于C臂的手术AR的精确校准过程是必不可少的,并且仍然具有挑战性。我们扩展了使用深度相机的现有方法,并提出了一种新的校准程序,该程序包括对C型臂成像系统的校准以及对RGB-D摄像机和C型臂系统进行3D / 2D校准的新方法,以实现可靠的数据和准确性高,同时与标准手术方案一致。对于校准程序,我们将束调整方程与3D设计的Lego多模态幻影一起应用,这与以前应用平面校准幻影的方法相反。通过使用我们的方法,在3D数据上完成了X射线图像的可视化,并且获得的平均覆盖误差为1.03 mm。评估表明,所提出的校准程序为AR手术提供了有希望的准确性,并且提高了现有的C臂校准方法(用于C臂和RGB-D传感器)的灵活性和耐用性。此外,结果表明我们的方法可以有效补偿C臂运动对校准参数的影响。结果表明,使用虚拟探测器可以改善C臂非零旋转运动的叠加误差。

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