Esfandiari Hooman, Lichti Derek, Anglin Carolyn
1 Department of Geomatics Engineering, University of Calgary, Calgary, AB, Canada.
2 University of British Columbia, Surgical Technologies Lab, Vancouver, BC, Canada.
Proc Inst Mech Eng H. 2017 Dec;231(12):1140-1151. doi: 10.1177/0954411917735556. Epub 2017 Oct 17.
This study provides a framework for a single-camera odometry system for localizing a surgical C-arm base. An application-specific monocular visual odometry system (a downward-looking consumer-grade camera rigidly attached to the C-arm base) is proposed in this research. The cumulative dead-reckoning estimation of the base is extracted based on frame-to-frame homography estimation. Optical-flow results are utilized to feed the odometry. Online positional and orientation parameters are then reported. Positional accuracy of better than 2% (of the total traveled distance) for most of the cases and 4% for all the cases studied and angular accuracy of better than 2% (of absolute cumulative changes in orientation) were achieved with this method. This study provides a robust and accurate tracking framework that not only can be integrated with the current C-arm joint-tracking system (i.e. TC-arm) but also is capable of being employed for similar applications in other fields (e.g. robotics).
本研究为用于定位手术C形臂基座的单相机里程计系统提供了一个框架。本研究提出了一种特定应用的单目视觉里程计系统（一个向下看的消费级相机，刚性连接到C形臂基座上）。基于帧间单应性估计提取基座的累积航位推算估计值。利用光流结果为里程计提供数据。然后报告在线位置和方向参数。使用该方法，在大多数情况下位置精度优于总行驶距离的2%，在所研究的所有情况下为4%，角度精度优于方向绝对累积变化的2%。本研究提供了一个强大且准确的跟踪框架，该框架不仅可以与当前的C形臂关节跟踪系统（即TC形臂）集成，还能够用于其他领域的类似应用（如机器人技术）。
