Monocular Endoscopic Tissue 3D Reconstruction with Multi-Level Geometry Regularization

• URL: http://arxiv.org/abs/2602.20718v1
• Date: Tue, 24 Feb 2026 09:29:36 GMT
• Title: Monocular Endoscopic Tissue 3D Reconstruction with Multi-Level Geometry Regularization
• Authors: Yangsen Chen, Hao Wang,
• Abstract summary: We introduce a novel approach based on 3D Gaussian Splatting to reconstruct soft endoscopic tissues.<n>Our proposed method delivers a fast rendering process and smooth surface appearances.
• Score: 3.696132675621222
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Reconstructing deformable endoscopic tissues is crucial for achieving robot-assisted surgery. However, 3D Gaussian Splatting-based approaches encounter challenges in achieving consistent tissue surface reconstruction, while existing NeRF-based methods lack real-time rendering capabilities. In pursuit of both smooth deformable surfaces and real-time rendering, we introduce a novel approach based on 3D Gaussian Splatting. Specifically, we introduce surface-aware reconstruction, initially employing a Sign Distance Field-based method to construct a mesh, subsequently utilizing this mesh to constrain the Gaussian Splatting reconstruction process. Furthermore, to ensure the generation of physically plausible deformations, we incorporate local rigidity and global non-rigidity restrictions to guide Gaussian deformation, tailored for the highly deformable nature of soft endoscopic tissue. Based on 3D Gaussian Splatting, our proposed method delivers a fast rendering process and smooth surface appearances. Quantitative and qualitative analysis against alternative methodologies shows that our approach achieves solid reconstruction quality in both textures and geometries.

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