SurGSplat: Progressive Geometry-Constrained Gaussian Splatting for Surgical Scene Reconstruction
Journal:
arXiv
Published Date:
Jun 6, 2025
Abstract
Intraoperative navigation relies heavily on precise 3D reconstruction to
ensure accuracy and safety during surgical procedures. However, endoscopic
scenarios present unique challenges, including sparse features and inconsistent
lighting, which render many existing Structure-from-Motion (SfM)-based methods
inadequate and prone to reconstruction failure. To mitigate these constraints,
we propose SurGSplat, a novel paradigm designed to progressively refine 3D
Gaussian Splatting (3DGS) through the integration of geometric constraints. By
enabling the detailed reconstruction of vascular structures and other critical
features, SurGSplat provides surgeons with enhanced visual clarity,
facilitating precise intraoperative decision-making. Experimental evaluations
demonstrate that SurGSplat achieves superior performance in both novel view
synthesis (NVS) and pose estimation accuracy, establishing it as a
high-fidelity and efficient solution for surgical scene reconstruction. More
information and results can be found on the page https://surgsplat.github.io/.
