Chu Yakui, Li Xu, Yang Xilin, Ai Danni, Huang Yong, Song Hong, Jiang Yurong, Wang Yongtian, Chen Xiaohong, Yang Jian
Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing 100081, China.
School of Software, Beijing Institute of Technology, Beijing 100081, China.
Biomed Opt Express. 2018 Oct 4;9(11):5205-5226. doi: 10.1364/BOE.9.005205. eCollection 2018 Nov 1.
Misleading depth perception may greatly affect the correct identification of complex structures in image-guided surgery. In this study, we propose a novel importance-driven hybrid rendering method to enhance perception for navigated endoscopic surgery. First, the volume structures are enhanced using gradient-based shading to reduce the color information in low-priority regions and improve the distinctions between complicated structures. Second, an importance sorting method based on the order-independent transparency rendering is introduced to intensify the perception of multiple surfaces. Third, volume data are adaptively truncated and emphasized with respect to the perspective orientation and the illustration of critical information for viewing range extension. Various experimental results prove that with the combination of volume and surface rendering, our method can effectively improve the depth distinction of multiple objects both in simulated and clinical scenes. Our importance-driven surface rendering method demonstrates improved average performance and statistical significance as rated by 15 participants (five clinicians and ten non-clinicians) on a five-point Likert scale. Further, the average frame rate of hybrid rendering with thin-layer sectioning reaches 42 fps. Given that the process of the hybrid rendering is fully automatic, it can be utilized in real-time surgical navigation to improve the rendering efficiency and information validity.
误导性的深度感知可能会极大地影响图像引导手术中复杂结构的正确识别。在本研究中，我们提出了一种新颖的重要性驱动混合渲染方法，以增强导航内镜手术的感知效果。首先，使用基于梯度的阴影增强体结构，以减少低优先级区域的颜色信息，并提高复杂结构之间的区分度。其次，引入一种基于顺序无关透明度渲染的重要性排序方法，以强化对多个表面的感知。第三，根据视角方向自适应地截断和强调体数据，并展示关键信息以扩展观察范围。各种实验结果证明，通过体渲染和表面渲染相结合，我们的方法能够在模拟场景和临床场景中有效提高多个物体的深度区分度。我们的重要性驱动表面渲染方法在15名参与者（5名临床医生和10名非临床医生）基于五点李克特量表的评分中显示出平均性能的提升和统计学意义。此外，薄层切片混合渲染的平均帧率达到42帧/秒。鉴于混合渲染过程是完全自动执行的，它可用于实时手术导航，以提高渲染效率和信息有效性。
