title: Principal component analysis in construction of 3D human knee joint models using a statistical shape model method.
abstract: 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 ± 0.81 mm, 0.34 ± 0.79 mm and 0.36 ± 0.59 mm for the femur, tibia and patella, respectively (average ± standard deviation). The computational time for each bone of the knee joint was within 30 s 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.
authors.affiliation: a Bioengineering Laboratory, Department of Orthopaedic Surgery , Massachusetts General Hospital, Harvard Medical School , 55 Fruit Street, GRJ-1215, Boston , MA 02114 , USA.
authors.forename: Tsung-Yuan
authors.initials: TY
authors.lastname: Tsai
authors.forename: Jing-Sheng
authors.initials: JS
authors.lastname: Li
authors.forename: Shaobai
authors.initials: S
authors.lastname: Wang
authors.forename: Pingyue
authors.initials: P
authors.lastname: Li
authors.forename: Young-Min
authors.initials: YM
authors.lastname: Kwon
authors.forename: Guoan
authors.initials: G
authors.lastname: Li
mesh_terms: D005269:Femur / Q000000981:diagnostic imaging; D005471:Fluoroscopy / Q000379:methods; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007717:Knee / Q000000981:diagnostic imaging; D007719:Knee Joint / Q000033:anatomy & histology* / Q000601:surgery; D015233:Models, Statistical; D010329:Patella / Q000000981:diagnostic imaging; D025341:Principal Component Analysis; D025321:Surgery, Computer-Assisted / Q000379:methods*; D013977:Tibia / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods
keywords: 3D knee model; fluoroscopic images; knee; statistical shape model