用动态高斯点云重建结肠镜下蠕动运动，提升手术导航精度。
ColonSplat: Reconstruction of Peristaltic Motion in Colonoscopy with Dynamic Gaussian Splatting
- 引入动态高斯点云，随结肠蠕动同步调整位置与形态。
- 在C3VDv2和DynamicColon数据集上实现更优几何保真度。
- 自建合成数据集DynamicColon，支持真实运动评估。
准确重建结肠镜检查中复杂的蠕动运动，对高级手术导航和回顾性诊断至关重要。尽管近期新视角合成与三维重建方法在一般内窥镜场景中表现优异，但在结肠这一高度受限的环境中仍面临挑战。由于摄像头在主动变形的管状结构中移动，视野有限，现有方法仅能重建初始相机轨迹下的结肠外观；而底层解剖结构基本保持静态，这些方法通过旋转、缩放或透明度调整来编码形变，而非更新高斯点的空间坐标（xyz）。本文首次对最先进的动态内窥镜方法在真实结肠镜场景中的表现进行基准分析，发现其无法建模真实的解剖运动。为实现对全局重建质量的严格评估，我们构建了DynamicColon合成数据集，包含每帧的真值点云。基于此，提出ColonSplat框架，能够捕捉类似蠕动的运动并保持全局几何一致性，在C3VDv2和DynamicColon数据集上均取得更优几何保真度。
原文摘要 · Abstract (English)
Accurate 3D reconstruction of colonoscopy data, accounting for complex peristaltic movements, is crucial for advanced surgical navigation and retrospective diagnostics. While recent novel view synthesis and 3D reconstruction methods have demonstrated remarkable success in general endoscopic scenarios, they struggle in the highly constrained environment of the colon. Due to the limited field of view of a camera moving through an actively deforming tubular structure, existing endoscopic methods reconstruct the colon appearance only for initial camera trajectory. However, the underlying anatomy remains largely static; instead of updating Gaussians' spatial coordinates (xyz), these methods encode deformation through either rotation, scale or opacity adjustments. In this paper, we first present a benchmark analysis of state-of-the-art dynamic endoscopic methods for realistic colonoscopic scenes, showing that they fail to model true anatomical motion. To enable rigorous evaluation of global reconstruction quality, we introduce DynamicColon, a synthetic dataset with ground-truth point clouds at every timestep. Building on these insights, we propose ColonSplat, a dynamic Gaussian Splatting framework that captures peristaltic-like motion while preserving global geometric consistency, achieving superior geometric fidelity on C3VDv2 and DynamicColon datasets. Project page: https://wmito.github.io/ColonSplat
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