# Dynamic Reconstruction of Deformable Soft-tissue with Stereo Scope in Minimal Invasive Surgery

arXiv: https://arxiv.org/abs/2003.10867 · HTML: https://mlsanity.com/paper/2003.10867/

## Key facts

- Cited by 23 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Mar 2020.

## Built on by (most cited first, 23 of 23)

- [Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery](https://mlsanity.com/paper/2206.15255/) (2022)
- [Endo-Depth-and-Motion: Reconstruction and Tracking in Endoscopic Videos using Depth Networks and Photometric Constraints](https://mlsanity.com/paper/2103.16525/) (2021)
- [EndoSurf: Neural Surface Reconstruction of Deformable Tissues with Stereo Endoscope Videos](https://mlsanity.com/paper/2307.11307/) (2023)
- [EndoGS: Deformable Endoscopic Tissues Reconstruction with Gaussian Splatting](https://mlsanity.com/paper/2401.11535/) (2024)
- [EndoGaussian: Real-time Gaussian Splatting for Dynamic Endoscopic Scene Reconstruction](https://mlsanity.com/paper/2401.12561/) (2024)
- [LGS: A Light-weight 4D Gaussian Splatting for Efficient Surgical Scene Reconstruction](https://mlsanity.com/paper/2406.16073/) (2024)
- [Efficient Deformable Tissue Reconstruction via Orthogonal Neural Plane](https://mlsanity.com/paper/2312.15253/) (2023)
- [EndoSparse: Real-Time Sparse View Synthesis of Endoscopic Scenes using Gaussian Splatting](https://mlsanity.com/paper/2407.01029/) (2024)
- [SurgicalGS: Dynamic 3D Gaussian Splatting for Accurate Robotic-Assisted Surgical Scene Reconstruction](https://mlsanity.com/paper/2410.09292/) (2024)
- [SurgicalGaussian: Deformable 3D Gaussians for High-Fidelity Surgical Scene Reconstruction](https://mlsanity.com/paper/2407.05023/) (2024)
- [Tracking monocular camera pose and deformation for SLAM inside the human body](https://mlsanity.com/paper/2204.08309/) (2022)
- [BDIS: Bayesian Dense Inverse Searching Method for Real-Time Stereo Surgical Image Matching](https://mlsanity.com/paper/2205.03133/) (2022)
- [Bayesian dense inverse searching algorithm for real-time stereo matching in minimally invasive surgery](https://mlsanity.com/paper/2106.07136/) (2021)
- [FLex: Joint Pose and Dynamic Radiance Fields Optimization for Stereo Endoscopic Videos](https://mlsanity.com/paper/2403.12198/) (2024)
- [BDIS-SLAM: A lightweight CPU-based dense stereo SLAM for surgery](https://mlsanity.com/paper/2312.15679/) (2023)
- [Neural Fields for 3D Tracking of Anatomy and Surgical Instruments in Monocular Laparoscopic Video Clips](https://mlsanity.com/paper/2403.19265/) (2024)
- [Diff2DGS: Reliable Reconstruction of Occluded Surgical Scenes via 2D Gaussian Splatting](https://mlsanity.com/paper/2602.18314/) (2026)
- [Free-DyGS: Camera-Pose-Free Scene Reconstruction for Dynamic Surgical Videos with Gaussian Splatting](https://mlsanity.com/paper/2409.01003/) (2024)
- [Tracking-Aware Deformation Field Estimation for Non-rigid 3D Reconstruction in Robotic Surgeries](https://mlsanity.com/paper/2503.02558/) (2025)
- [Feature-EndoGaussian: Feature Distilled Gaussian Splatting in Surgical Deformable Scene Reconstruction](https://mlsanity.com/paper/2503.06161/) (2025)
- [ColorGS: High-fidelity Surgical Scene Reconstruction with Colored Gaussian Splatting](https://mlsanity.com/paper/2508.18696/) (2025)
- [SAGS: Self-Adaptive Alias-Free Gaussian Splatting for Dynamic Surgical Endoscopic Reconstruction](https://mlsanity.com/paper/2510.27318/) (2025)
- [Monocular Endoscopic Tissue 3D Reconstruction with Multi-Level Geometry Regularization](https://mlsanity.com/paper/2602.20718/) (2026)

## Abstract (arXiv)

In minimal invasive surgery, it is important to rebuild and visualize the latest deformed shape of soft-tissue surfaces to mitigate tissue damages. This paper proposes an innovative Simultaneous Localization and Mapping (SLAM) algorithm for deformable dense reconstruction of surfaces using a sequence of images from a stereoscope. We introduce a warping field based on the Embedded Deformation (ED) nodes with 3D shapes recovered from consecutive pairs of stereo images. The warping field is estimated by deforming the last updated model to the current live model. Our SLAM system can: (1) Incrementally build a live model by progressively fusing new observations with vivid accurate texture. (2) Estimate the deformed shape of unobserved region with the principle As-Rigid-As-Possible. (3) Show the consecutive shape of models. (4) Estimate the current relative pose between the soft-tissue and the scope. In-vivo experiments with publicly available datasets demonstrate that the 3D models can be incrementally built for different soft-tissues with different deformations from sequences of stereo images obtained by laparoscopes. Results show the potential clinical application of our SLAM system for providing surgeon useful shape and texture information in minimal invasive surgery.