MV-dVRK：面向空间手术感知的多视点基准
MV-dVRK: A Multi-Viewpoint Benchmark for Spatial Surgical Perception
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中文总结 AI 辅助
本文提出首个离体手术多视点基准MV-dVRK，含静态与动态手术数据，用于对比不同三维重建方法，发现多视点优化方法在1mm容差下覆盖67%真实表面点，优于前馈基础模型的43%。
中文摘要 AI 辅助
大规模训练与精细优化技术已大幅提升稀疏多视点三维重建性能，但这类方法虽与手术高度相关，却从未在真实内镜图像上接受过严格评估。当前临床遥控机器人在患者体内部署单目立体相机，导致多视点数据极为稀缺。本文提出MV-dVRK，首个离体手术数据集，结合多曝光同步立体视点、精确表面几何与相机位姿。该基准的静态子集提供经工业3D扫描仪验证的密集SfM参考几何，以及真实相机位姿与稀疏视点测试集。我们利用MV-dVRK系统对比零样本单目、立体、多立体及多视点三维重建方法随视点数量增加的表现：使用两台内镜时，多立体重建覆盖率最高；加入第三视点后，基于优化的多视点方法表现最佳，在1毫米容差内覆盖67%的真实表面点，且恢复高精度相对相机位姿；相比之下，前馈基础模型在相同设置下仅覆盖43%的真实表面。MV-dVRK还包含10个涵盖多种手术任务的动态序列，具备不断提升的运动复杂度与组织形变，为未来多视点手术感知研究提供基础。该项目可访问：this https URL。
英文摘要
Large-scale training and refined optimization techniques have greatly improved sparse multi-view 3D reconstruction. Despite their relevance to surgery, such methods have never before been rigorously evaluated on real endoscopic images. Current clinical telerobots deploy a single stereo camera inside the patient, making multi-viewpoint data extremely rare. This paper presents MV-dVRK, the first ex-vivo surgical dataset to combine multiple exposure-synchronized stereo viewpoints with accurate surface geometry and camera poses. The static subset of the benchmark provides dense SfM reference geometry, validated against an industrial 3D scanner, together with ground-truth camera poses and sparse-view test sets. We use MV-dVRK to systematically compare zero-shot monocular, stereo, multi-stereo, and multi-view 3D reconstruction methods as the number of viewpoints increases. With two endoscopes, multi-stereo reconstruction achieves the highest coverage. With a third viewpoint, optimization-based multi-view methods perform best, covering 67% of ground-truth surface points within a 1 mm tolerance and recovering highly accurate relative camera poses. By contrast, feed-forward foundation models cover only 43% of the ground-truth surface in the same setting. MV-dVRK also includes ten dynamic sequences spanning multiple surgical tasks, with increasing kinematic complexity and tissue deformation, providing a basis for future research in multi-viewpoint surgical perception. The project is available at: https://mv-dvrk.is.mpg.de.
发表机构
- Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）
- ETH Zürich（苏黎世联邦理工学院）
- Erbe Group（爱尔博集团）
- Tübingen University Hospital（蒂宾根大学医院）
- Johns Hopkins University（约翰霍普金斯大学）
机构由 AI 辅助整理，请以论文原文为准。
