Towards Multiple 3D Bone Surface Identification and Reconstruction Using Few 2D X-Ray Images for Intraoperative Applications

S. Prakoonwit
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引用次数: 6

Abstract

This article discusses a possible method to use a small number, e.g. 5, of conventional 2D X-ray images to reconstruct multiple 3D bone surfaces intraoperatively. Each bone's edge contours in X-ray images are automatically identified. Sparse 3D landmark points of each bone are automatically reconstructed by pairing the 2D X-ray images. The reconstructed landmark point distribution on a surface is approximately optimal covering main characteristics of the surface. A statistical shape model, dense point distribution model (DPDM), is then used to fit the reconstructed optimal landmarks vertices to reconstruct a full surface of each bone separately. The reconstructed surfaces can then be visualised and manipulated by surgeons or used by surgical robotic systems.
基于少量二维x线图像的多三维骨表面识别与重建在术中应用
本文讨论了一种可能的方法,即术中使用少量(例如5张)常规2D x线图像重建多个3D骨表面。x射线图像中每个骨骼的边缘轮廓自动识别。通过对二维x射线图像进行配对,自动重建每个骨骼的稀疏三维地标点。重建的曲面上的地标点分布近似最优,覆盖了曲面的主要特征。然后使用统计形状模型,密集点分布模型(DPDM)来拟合重建的最佳地标顶点,以分别重建每个骨骼的完整表面。然后,重建的表面可以被外科医生可视化和操作,或者被外科机器人系统使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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