摘要
背景:基于CT图像的髋关节分割技术已广泛应用于计算机辅助手术规划、假体设计和有限元分析。目的:探讨基于贝叶斯决策的髋关节自动分割方法在计算机辅助髋关节手术中的应用效果。方法:针对髋关节序列CT图像中骨骼近端分割精度低,计算复杂度高,自动化程度低等问题,提出了一种自动分割算法,通过对比度增强、阈值分割和区域增长等算法提取股骨的初步轮廓,再根据贝叶斯决策论对股骨边缘进行再次分割。结果与结论:基于贝叶斯决策的髋关节自动分割方法计算速度快,鲁棒性高,分割准确,在计算机辅助髋关节手术及假体设计等方面具有一定的实用价值。
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 challenging 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.
出处
《中国组织工程研究》
CAS
北大核心
2016年第39期5873-5878,共6页
Chinese Journal of Tissue Engineering Research
