无需标记的脊柱软组织术中追踪，提升手术效率与精度。
Towards Markerless Intraoperative Tracking of Deformable Spine Tissue
- 基于消费级深度相机实现无标记脊柱追踪
- 构建首个真实临床脊柱手术RGB-D数据集
- 提出多任务网络预测配准关键区域，适用于术中实时应用
利用消费级RGB-D相机进行术中骨科组织追踪具有高转化潜力。与依赖骨钉标记的设备相比，无标记追踪可减少手术时间和操作复杂度。然而，现有研究仅限于尸体实验。本文首次发布真实临床脊柱手术的RGB-D数据集，并提出SpineAlign系统，用于捕捉术前与术中脊柱形态的形变。同时，基于该数据集训练了术中分割网络，并引入CorrespondNet——一种多任务框架，可同时预测术中与术前场景中的配准关键区域。
原文摘要 · Abstract (English)
Consumer-grade RGB-D imaging for intraoperative orthopedic tissue tracking is a promising method with high translational potential. Unlike bone-mounted tracking devices, markerless tracking can reduce operating time and complexity. However, its use has been limited to cadaveric studies. This paper introduces the first real-world clinical RGB-D dataset for spine surgery and develops SpineAlign, a system for capturing deformation between preoperative and intraoperative spine states. We also present an intraoperative segmentation network trained on this data and introduce CorrespondNet, a multi-task framework for predicting key regions for registration in both intraoperative and preoperative scenes.
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