Deform3DGS: Flexible Deformation for Fast Surgical Scene Reconstruction with Gaussian Splatting

TL;DR

Deform3DGS introduces a fast, real-time surgical scene reconstruction method using Gaussian Splatting and a novel deformation model, significantly improving speed and fidelity for intraoperative use.

Contribution

The paper presents a new flexible deformation modeling scheme integrated with Gaussian Splatting for rapid, high-fidelity surgical scene reconstruction during endoscopic procedures.

Findings

Achieves 338.8 FPS rendering speed.

Reduces training time to 1 minute per scene.

Demonstrates superior reconstruction quality on surgical videos.

Abstract

Tissue deformation poses a key challenge for accurate surgical scene reconstruction. Despite yielding high reconstruction quality, existing methods suffer from slow rendering speeds and long training times, limiting their intraoperative applicability. Motivated by recent progress in 3D Gaussian Splatting, an emerging technology in real-time 3D rendering, this work presents a novel fast reconstruction framework, termed Deform3DGS, for deformable tissues during endoscopic surgery. Specifically, we introduce 3D GS into surgical scenes by integrating a point cloud initialization to improve reconstruction. Furthermore, we propose a novel flexible deformation modeling scheme (FDM) to learn tissue deformation dynamics at the level of individual Gaussians. Our FDM can model the surface deformation with efficient representations, allowing for real-time rendering performance. More importantly, FDM significantly accelerates surgical scene reconstruction, demonstrating considerable clinical values, particularly in intraoperative settings where time efficiency is crucial. Experiments on DaVinci robotic surgery videos indicate the efficacy of our approach, showcasing superior reconstruction fidelity PSNR: (37.90) and rendering speed (338.8 FPS) while substantially reducing training time to only 1 minute/scene. Our code is available at https://github.com/jinlab-imvr/Deform3DGS.