Mirota Daniel, Wang Hanzi, Taylor Russell H, Ishii Masaru, Hager Gregory D
Department of Computer Science, The Johns Hopkins University, Baltimore, MD, USA.
Med Image Comput Comput Assist Interv. 2009 Jan 1;5761:91-99. doi: 10.1007/978-3-642-04268-3_12.
Endoscopic endonasal skull base surgery (ESBS) requires high accuracy to ensure safe navigation of the critical anatomy at the anterior skull base. Current navigation systems provide approximately 2mm accuracy. This level of registration error is due in part from the indirect nature of tracking used. We propose a method to directly track the position of the endoscope using video data. Our method first reconstructs image feature points from video in 3D, and then registers the reconstructed point cloud to pre-operative data (e.g. CT/MRI). After the initial registration, the system tracks image features and maintains the 2D-3D correspondence of image features and 3D locations. These data are then used to update the current camera pose. We present registration results within 1mm, which matches the accuracy of our validation framework.
鼻内镜下颅底手术（ESBS）需要高精度以确保在前颅底关键解剖结构中的安全导航。当前的导航系统提供约2毫米的精度。这种配准误差水平部分归因于所使用跟踪方法的间接性质。我们提出了一种利用视频数据直接跟踪内窥镜位置的方法。我们的方法首先从视频中三维重建图像特征点，然后将重建的点云与术前数据（如CT/MRI）进行配准。初始配准后，系统跟踪图像特征并维持图像特征与三维位置的二维-三维对应关系。然后利用这些数据更新当前相机姿态。我们展示了误差在1毫米以内的配准结果，这与我们验证框架的精度相匹配。
