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Towards webcam-based tracking for interventional navigation

机译:迈向基于网络摄像头的介入导航跟踪

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PURPOSE: Optical tracking is a commonly used tool in computer assisted surgery and surgical training; however, many current generation commercially available tracking systems are prohibitively large and expensive for certain applications. We developed an open source optical tracking system using the Intel RealSense SR300 webcam with integrated depth sensor. In this paper, we assess the accuracy of this tracking system. METHODS: The PLUS toolkit was extended to incorporate the ArUco marker detection and tracking library. The depth data obtained from the infrared sensor of the Intel RealSense SR300 was used to improve accuracy. We assessed the accuracy of the system by comparing this tracker to a high accuracy commercial optical tracker. RESULTS: The ArUco based optical tracking algorithm had median errors of 20.0mm and 4.1 degrees in a 200x200x200mm tracking volume. Our algorithm processing the depth data had a positional error of 17.3mm, and an orientation error of 7.1 degrees in the same tracking volume. In the direction perpendicular to the sensor, the optical only tracking had positional errors between 11% and 15%, compared to errors in depth of 1% or less. In tracking one marker relative to another, a fused transform from optical and depth data produced the best result of 1.39% error. CONCLUSION: The webcam based system does not yet have satisfactory accuracy for use in computer assisted surgery or surgical training.
机译:目的:光学跟踪是计算机辅助手术和手术培训中常用的工具;然而,对于某些应用,许多当前市场上可买到的跟踪系统过大且昂贵。我们使用带集成深度传感器的英特尔实感SR300网络摄像头开发了一个开源光学跟踪系统。在本文中,我们评估了此跟踪系统的准确性。方法:PLUS工具包已扩展为包含ArUco标记检测和跟踪库。从英特尔实感SR300的红外传感器获得的深度数据用于提高精度。我们通过将该跟踪器与高精度商用光学跟踪器进行比较来评估系统的准确性。结果:基于ArUco的光学跟踪算法在200x200x200mm的跟踪体积中具有20.0mm和4.1度的中值误差。在相同的跟踪体积中,我们处理深度数据的算法的位置误差为17.3mm,方向误差为7.1度。在垂直于传感器的方向上,仅光学跟踪的位置误差在11%到15%之间,而深度误差为1%或更小。在跟踪一个标记相对于另一个标记时,来自光学和深度数据的融合变换产生了1.39%误差的最佳结果。结论:基于网络摄像头的系统在计算机辅助手术或手术培训中使用的准确性尚不令人满意。

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