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Related Concept Videos

Transformation of Plane Strain01:12

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Related Experiment Video

Updated: Jan 9, 2026

Photorealistic Learned Landscapes for Augmented Reality
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SurGSplat: Progressive Geometry-Constrained Gaussian Splatting for Surgical Scene Reconstruction.

Yuchao Zheng, Jianing Zhang, Guochen Ning

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed
    Summary

    This study introduces SurGSplat, a new method for 3D reconstruction in surgery using geometric constraints to improve 3D Gaussian Splatting (3DGS). It enhances surgical navigation accuracy and visual clarity for better intraoperative decision-making.

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    Area of Science:

    • Medical Imaging and Computer-Aided Surgery
    • 3D Reconstruction Technologies
    • Surgical Navigation Systems

    Background:

    • Intraoperative navigation demands accurate 3D reconstruction for surgical safety.
    • Endoscopic surgery poses challenges like sparse features and poor lighting, limiting existing Structure-from-Motion (SfM) methods.
    • Current methods often fail in complex surgical environments, impacting navigation precision.

    Purpose of the Study:

    • To develop a robust 3D reconstruction method for endoscopic surgical navigation.
    • To enhance the accuracy and reliability of 3D scene reconstruction in challenging surgical conditions.
    • To improve surgeons' visual clarity and decision-making capabilities during procedures.

    Main Methods:

    • Proposed SurGSplat, a novel paradigm integrating geometric constraints with 3D Gaussian Splatting (3DGS).
    • Progressively refined 3DGS to overcome limitations of SfM-based techniques in sparse and poorly lit environments.
    • Focused on detailed reconstruction of critical anatomical features, such as vascular structures.

    Main Results:

    • SurGSplat demonstrated superior performance in novel view synthesis (NVS).
    • Achieved higher pose estimation accuracy compared to existing methods.
    • Provided high-fidelity and efficient surgical scene reconstruction, enhancing visual clarity.

    Conclusions:

    • SurGSplat offers a high-fidelity and efficient solution for surgical scene reconstruction.
    • The method effectively addresses challenges in endoscopic scenarios, improving intraoperative navigation.
    • Enhanced visual clarity and reconstruction accuracy support precise surgical decision-making.