School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China.
Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, China.
Int J Med Robot. 2022 Feb;18(1):e2341. doi: 10.1002/rcs.2341. Epub 2021 Oct 22.
BACKGROUND: The existing augmented reality (AR) based neuronavigation systems typically require markers and additional tracking devices for model registration, which causes excessive preparatory steps. METHODS: For fast and accurate intraoperative navigation, this work proposes a marker-less AR system that tracks the head features with the monocular camera. After the semi-automatic initialization process, the feature points between the captured image and the pre-loaded keyframes are matched for obtaining correspondences. The camera pose is estimated by solving the Perspective-n-Point problem. RESULTS: The localization error of AR visualization on scalp and falx meningioma is 0.417 ± 0.057 and 1.413 ± 0.282 mm, respectively. The maximum localization error is less than 2 mm. The AR system is robust to occlusions and changes in viewpoint and scale. CONCLUSIONS: We demonstrate that the developed system can successfully display the augmented falx meningioma with enough accuracy and provide guidance for neurosurgeons to locate the tumour in brain.
背景:现有的基于增强现实(AR)的神经导航系统通常需要标记物和额外的跟踪设备来进行模型注册,这导致了过多的预备步骤。
方法:为了实现快速准确的术中导航,本工作提出了一种无需标记物的 AR 系统,该系统使用单目相机跟踪头部特征。在半自动初始化过程之后,通过匹配捕获图像和预加载关键帧之间的特征点来获取对应关系。通过求解透视 n 点问题来估计相机姿态。
结果:AR 可视化在头皮和镰状脑膜瘤上的定位误差分别为 0.417 ± 0.057 和 1.413 ± 0.282 毫米,最大定位误差小于 2 毫米。该 AR 系统对遮挡、视角和比例变化具有鲁棒性。
结论:我们证明了所开发的系统可以成功地显示增强的镰状脑膜瘤,并且具有足够的准确性,可以为神经外科医生定位脑部肿瘤提供指导。
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