Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada.
Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON M5S, Canada.
J Clin Neurosci. 2020 Feb;72:392-396. doi: 10.1016/j.jocn.2019.12.014. Epub 2019 Dec 28.
Computer assisted navigation (CAN) is a technology which has been available for commercial use in operating rooms for quite some time now. CAN relies on the information presented in patient imaging (usually CT or MRI images) and the surgical site. The method for registration between these two sets of data is crucial for safe image guided navigation during surgery. Although the existing technologies are extremely accurate, they still pose problems in the operating. Motivation for this study is to explore the possibility of using augmented reality (AR) to improve ease of use for surgical navigation and provide a system which complements the existing operating room workflow. As with all commercially available surgical navigation systems, registration accuracy is of utmost important to maintain patient safety. In this paper, we propose a novel method to quantify registration accuracy for augmented reality (AR) devices in neurosurgery.
计算机辅助导航（CAN）是一种已经在手术室中商业化使用了相当一段时间的技术。CAN 依赖于患者成像（通常是 CT 或 MRI 图像）和手术部位的信息。这两组数据之间的配准方法对于手术期间安全的图像引导导航至关重要。尽管现有的技术非常精确，但它们在手术中仍然存在问题。本研究的动机是探索使用增强现实（AR）来提高手术导航的易用性并提供补充现有手术室工作流程的系统的可能性。与所有市售的手术导航系统一样，注册准确性对于维护患者安全至关重要。在本文中，我们提出了一种用于神经外科的增强现实（AR）设备的注册准确性的新方法。
