Dynamic scene reconstruction is essential in robotic minimally invasive surgery, providing crucial spatial information that enhances surgical precision and outcomes. However, existing methods struggle to address the complex, temporally dynamic nature of endoscopic scenes. This paper presents ST-Endo4DGS, a novel framework that models the spatio-temporal volume of dynamic endoscopic scenes using unbiased 4D Gaussian Splatting (4DGS) primitives, parameterized by anisotropic ellipses with flexible 4D rotations. This approach enables precise representation of deformable tissue dynamics, capturing intricate spatial and temporal correlations in real time. Additionally, we extend spherindrical harmonics to represent time-evolving appearance, achieving realistic adaptations to lighting and view changes. A new endoscopic normal alignment constraint (ENAC) further enhances geometric fidelity by aligning rendered normals with depth-derived geometry. Extensive evaluations show that ST-Endo4DGS outperforms existing methods in both visual quality and real-time performance, establishing a new state-of-the-art in dynamic scene reconstruction for endoscopic surgery.
动态场景重建在机器人微创手术中至关重要，为提升手术精度和效果提供了关键的空间信息。然而，现有方法难以应对内窥镜场景复杂且时间动态的特性。本文提出了一种新框架——ST-Endo4DGS，使用无偏的4D高斯散点（4DGS）基元建模动态内窥镜场景的时空体积，基元通过各向异性椭球体表示，并支持灵活的4D旋转。该方法能够精确表示可变形组织的动态，实时捕捉复杂的空间和时间相关性。此外，我们扩展了球面谐波以表示随时间变化的外观，实现了对光照和视角变化的真实适应。新引入的内窥镜法线对齐约束（ENAC）通过将渲染法线与深度派生几何对齐，进一步增强了几何精度。大量评估结果表明，ST-Endo4DGS在视觉质量和实时性能方面优于现有方法，确立了内窥镜手术动态场景重建的新先进标准。