Automatic segmentation method for hip joint based on Bayesian Decision Theory
10.3969/j.issn.2095-4344.2016.39.015
- VernacularTitle:基于贝叶斯决策的髋关节自动分割方法
- Author:
Anbang MA
;
Dong WANG
;
Huihui WU
;
Kerong DAI
;
Dongyun GU
- Publication Type:Journal Article
- From:
Chinese Journal of Tissue Engineering Research
2016;20(39):5873-5878
- CountryChina
- Language:Chinese
-
Abstract:
BACKGROUND:Hip segmentation based on CT image has been widely used in computer-assisted surgery planning, prosthesis design and finite element analysis. OBJECTIVE:To explore application effects of automatic segmentation method for hip joint based on Bayesian Decision Theory in computer-assisted hip surgery. METHODS:An accurate outer surface segmentation and extraction remain chal enging due to deformed shapes and extremely narrow inter-bone regions. In this paper, we present an automatic, fast and accurate approach for segmentation of femoral head and proximal acetabulum. The outline of the femur was segmented and extracted by contrast enhancement, thresholding algorithm and region growth algorithm. The boundaries of the bone regions are further refined based on Bayes decision rule. RESULTS AND CONCLUSION:Automatic segmentation method for hip joint based on Bayesian Decision Theory is an accurate segmentation technique for femoral head and proximal acetabulum and it can be applied in computer-assisted hip surgery and prosthesis design.
