New Medical Image Sequences Segmentation Based on Level Set Method

摘要：

Image segmentation is one of the key problems in medical image processing. The level set method based on curves evolving theory and partial differential equation theory is widely applied in the segmentation of medical image. The level set method can handle topology changes effectively. In this paper, a penalized energy is added into the geodesic active contour (GAC) model and the C_V model respectively to eliminate the reinitialization procedure completely. Then, a term of boundary information is added into the C_V model to incorporate regional and gradient information together for better segmentation. The segmentation for medical image sequence which is implemented in this paper is the necessary preparation for 3D reconstruction later on. The obtained results have shown desirable segmentation performance.

关键词： Level Set Method Re-initialization Geodesic Active Contour Model C_V Model Medical Image Segmentation

作者: Xujia Qin Suqiong Zhang

作者单位: College of Software, Zhejiang University of Technology Hangzhou, 310032, China

会议类型: 国际会议

会议名称: 2009图像分析与信号处理国际会议(2009 International Conference on Image Analysis and Signal Processing)

会议地点: 浙江台州

会议语种:英文

页码: 22-27

在线出版日期: 2009-04-11（万方平台首次上网日期，不代表论文的发表时间）