Suppr超能文献

自动确定孤立人体膝关节三维骨骼模型的解剖坐标系。

Automatic determination of anatomical coordinate systems for three-dimensional bone models of the isolated human knee.

机构信息

Bioengineering Laboratory, Department of Orthopaedics, The Warren Alpert Medical School of Brown University/Rhode Island Hospital, CORO West, Suite 404, 1 Hoppin Street, Providence, RI 02903, USA.

出版信息

J Biomech. 2010 May 28;43(8):1623-6. doi: 10.1016/j.jbiomech.2010.01.036. Epub 2010 Feb 18.

Abstract

The combination of three-dimensional (3-D) models with dual fluoroscopy is increasingly popular for evaluating joint function in vivo. Applying these modalities to study knee motion with high accuracy requires reliable anatomical coordinate systems (ACSs) for the femur and tibia. Therefore, a robust method for creating ACSs from 3-D models of the femur and tibia is required. We present and evaluate an automated method for constructing ACSs for the distal femur and proximal tibia based solely on 3-D bone models. The algorithm requires no observer interactions and uses model cross-sectional area, center of mass, principal axes of inertia, and cylindrical surface fitting to construct the ACSs. The algorithm was applied to the femur and tibia of 10 (unpaired) human cadaveric knees. Due to the automated nature of the algorithm, the within specimen variability is zero for a given bone model. The algorithm's repeatability was evaluated by calculating variability in ACS location and orientation across specimens. Differences in ACS location and orientation between specimens were low (<1.5mm and <2.5 degrees). Variability arose primarily from natural anatomical and morphological differences between specimens. The presented algorithm provides an alternative method for automatically determining subject-specific ACSs from the distal femur and proximal tibia.

摘要

三维(3-D)模型与双荧光透视术的结合越来越受欢迎,可用于评估体内关节功能。将这些模式应用于研究膝关节运动,需要有可靠的股骨和胫骨解剖坐标系(ACS)。因此,需要一种从股骨和胫骨的 3-D 模型创建 ACS 的稳健方法。我们提出并评估了一种基于 3-D 骨骼模型,自动构建股骨远端和胫骨近端 ACS 的方法。该算法不需要观察者的交互作用,而是使用模型的横截面积、质心、惯性主轴和圆柱面拟合来构建 ACS。该算法应用于 10 个(非配对)人体尸体膝关节的股骨和胫骨。由于算法的自动化性质,对于给定的骨骼模型,给定骨骼模型的内部标本变异性为零。通过计算跨标本 ACS 位置和方向的变化来评估算法的可重复性。标本之间 ACS 位置和方向的差异较小(<1.5mm 和 <2.5 度)。差异主要来自标本之间的自然解剖和形态差异。所提出的算法为从股骨远端和胫骨近端自动确定特定于个体的 ACS 提供了一种替代方法。

相似文献

引用本文的文献

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验