Neuro-Oncology Clinic, National Cancer Center, Goyang, Republic of Korea.
Research and Science Division, Research and Development Center, MEDICALIP Co. Ltd., Seoul, Republic of Korea.
Int J Comput Assist Radiol Surg. 2024 Jan;19(1):15-25. doi: 10.1007/s11548-023-02993-0. Epub 2023 Jul 13.
Concomitant with the significant advances in computing technology, the utilization of augmented reality-based navigation in clinical applications is being actively researched. In this light, we developed novel object tracking and depth realization technologies to apply augmented reality-based neuronavigation to brain surgery.
We developed real-time inside-out tracking based on visual inertial odometry and a visual inertial simultaneous localization and mapping algorithm. The cube quick response marker and depth data obtained from light detection and ranging sensors are used for continuous tracking. For depth realization, order-independent transparency, clipping, and annotation and measurement functions were developed. In this study, the augmented reality model of a brain tumor patient was applied to its life-size three-dimensional (3D) printed model.
Using real-time inside-out tracking, we confirmed that the augmented reality model remained consistent with the 3D printed patient model without flutter, regardless of the movement of the visualization device. The coordination accuracy during real-time inside-out tracking was also validated. The average movement error of the X and Y axes was 0.34 ± 0.21 and 0.04 ± 0.08 mm, respectively. Further, the application of order-independent transparency with multilayer alpha blending and filtered alpha compositing improved the perception of overlapping internal brain structures. Clipping, and annotation and measurement functions were also developed to aid depth perception and worked perfectly during real-time coordination. We named this system METAMEDIP navigation.
The results validate the efficacy of the real-time inside-out tracking and depth realization technology. With these novel technologies developed for continuous tracking and depth perception in augmented reality environments, we are able to overcome the critical obstacles in the development of clinically applicable augmented reality neuronavigation.
随着计算技术的显著进步，基于增强现实的导航在临床应用中的应用正在积极研究。有鉴于此，我们开发了新的物体跟踪和深度实现技术，将基于增强现实的神经导航应用于脑外科手术。
我们开发了基于视觉惯性里程计和视觉惯性同时定位和地图绘制算法的实时内外跟踪。使用立方快速响应标记和来自光检测和测距传感器的深度数据进行连续跟踪。为了实现深度，开发了顺序无关的透明度、裁剪、注释和测量功能。在本研究中，脑肿瘤患者的增强现实模型被应用于其全尺寸三维（3D）打印模型。
使用实时内外跟踪，我们确认增强现实模型与 3D 打印的患者模型保持一致，没有颤动，无论可视化设备如何移动。还验证了实时内外跟踪的协调精度。X 和 Y 轴的平均运动误差分别为 0.34±0.21 和 0.04±0.08 毫米。此外，使用多层 alpha 混合和过滤 alpha 合成的顺序无关透明度提高了对重叠内部脑结构的感知。裁剪、注释和测量功能也被开发出来以帮助深度感知，并在实时协调中完美运行。我们将这个系统命名为 METAMEDIP 导航。
结果验证了实时内外跟踪和深度实现技术的有效性。通过为增强现实环境中的连续跟踪和深度感知开发这些新技术，我们能够克服开发临床应用增强现实神经导航的关键障碍。
