用4D高斯点云实时重建内窥镜动态场景，提升手术精度。
Real-Time Spatio-Temporal Reconstruction of Dynamic Endoscopic Scenes with 4D Gaussian Splatting
- 基于各向异性椭球的4D高斯点云建模动态组织变形。
- 实时渲染且视觉质量超越现有方法，支持光照与视角变化。
- 适合医疗影像、机器人手术系统开发人员参考。
动态场景重建在机器人微创手术中至关重要，能提供关键空间信息以提升手术精度和效果。然而，现有方法难以应对内窥镜场景复杂的时序动态特性。本文提出ST-Endo4DGS框架，采用无偏4D高斯点云（4DGS）原语，通过可变4D旋转的各向异性椭球参数化，精确建模动态内窥镜场景的时空体积，捕捉组织形变中的复杂时空关联，并实现实时渲染。此外，将球面谐波扩展至时变外观表示，实现对光照与视角变化的真实还原。引入新的内窥镜法向对齐约束（ENAC），通过将渲染法向与深度推导几何对齐，进一步提升几何保真度。大量实验表明，该方法在视觉质量和实时性能上均优于现有方法，确立了内窥镜手术动态场景重建的新基准。
原文摘要 · Abstract (English)
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.
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