Automatic extraction of proximal femur contours from calibrated X-ray images using 3D statistical models: an in vitro study
✍ Scribed by Xiao Dong; Guoyan Zheng
- Publisher
- Wiley (Robotic Publications)
- Year
- 2009
- Tongue
- English
- Weight
- 467 KB
- Volume
- 5
- Category
- Article
- ISSN
- 1478-5951
- DOI
- 10.1002/rcs.253
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✦ Synopsis
Abstract
Background
Accurate extraction of bone contours from two‐dimensional (2D) projective X‐ray images is an important component for computer‐assisted diagnosis, planning or three‐dimensional (3D) reconstruction.
Methods
We propose a 3D statistical model‐based, fully automatic segmentation framework for extracting the proximal femur contours from calibrated X‐ray images. The automatic initialization is an estimation of a Bayesian network algorithm to fit a multiple‐component geometrical model to the X‐ray data. The contour extraction is accomplished by a non‐rigid 2D/3D registration between the statistical model and the X‐ray images, in which bone contours are extracted by a graphical model‐based Bayesian inference.
Results
The contour extraction algorithm was verified on both cadaver and clinical datasets, visually and quantitatively. Compared to the ‘gold standard’, a mean error of 1.6 mm was observed when the automatically extracted contours were used to reconstruct a patient‐specific surface model.
Conclusions
Our statistical model‐based bone contour extraction approach holds the potential to facilitate the application of 2D/3D reconstruction in surgical navigation. Copyright © 2009 John Wiley & Sons, Ltd.