Principal component analysis in construction of 3D human knee joint models using a statistical shape model method

被引：18
作者：
Tsai, Tsung-Yuan [1 ]
Li, Jing-Sheng [1 ]
Wang, Shaobai [1 ]
Li, Pingyue [1 ,2 ]
Kwon, Young-Min [1 ]
Li, Guoan [1 ]
机构：
[1] Harvard Univ, Massachusetts Gen Hosp, Sch Med, Bioengn Lab,Dept Orthopaed Surg, Boston, MA 02114 USA
[2] Guangzhou Mil Command, Guangzhou Gen Hosp, Dept Orthopaed Surg, Guangzhou 510010, Guangdong, Peoples R China
来源：
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING | 2015年 / 18卷 / 07期
关键词：
fluoroscopic images; 3D knee model; statistical shape model; knee; PROXIMAL FEMUR; RECONSTRUCTION; SURFACE; REGISTRATION; IMAGES; ARTHROPLASTY; PELVIS;
D O I：
10.1080/10255842.2013.843676
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The statistical shape model (SSM) method that uses 2D images of the knee joint to predict the three-dimensional (3D) joint surface model has been reported in the literature. In this study, we constructed a SSM database using 152 human computed tomography (CT) knee joint models, including the femur, tibia and patella and analysed the characteristics of each principal component of the SSM. The surface models of two in vivo knees were predicted using the SSM and their 2D bi-plane fluoroscopic images. The predicted models were compared to their CT joint models. The differences between the predicted 3D knee joint surfaces and the CT image-based surfaces were 0.30 +/- 0.81mm, 0.34 +/- 0.79mm and 0.36 +/- 0.59mm for the femur, tibia and patella, respectively (average +/- standard deviation). The computational time for each bone of the knee joint was within 30s using a personal computer. The analysis of this study indicated that the SSM method could be a useful tool to construct 3D surface models of the knee with sub-millimeter accuracy in real time. Thus, it may have a broad application in computer-assisted knee surgeries that require 3D surface models of the knee.
引用
收藏
页码：721 / 729
页数：9
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