A Graph-Based Segmentation Method for 3D Ultrasound images

摘要：

As the 3D imaging techniques have been more and more widely applied in medical applications, analysis of 3D medical images becomes necessary. This paper presents a novel segmentation method for extracting objects of interest (OOI) in 3D ultrasound images. The proposed method taking advantage of graph theory to construct a 3D graph is called 3D graph-based segmentation algorithm. It can generate a set of minimum spanning trees each of which corresponds to a 3D sub-region. In comparison with a previously reported 3D active contour model (i.e. 3D Snake), our graph-based segmentation method is less computationally complex, hence resulting in less computation time. In terms of segmentation accuracy, the experimental results using an ultrasound phantom demonstrate that our method outperforms the 3D Snake and Fuzzy C Means clustering methods, indicating improved performance for potential clinical applications.

关键词： Graph theory 3D ultrasound image segmentation pairwise region comparison predicate snakes Fuzzy C means

作者: Lifang Zheng Qinghua Huang

作者单位: School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 4001-4005

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）