A Medical Image Segmentation Based on Global Variational Level Set

摘要：

　　A medical image segmentation based on global variables differential level set is proposed in this paper for medical images with complex topological structure,strong contrast and low noise characteristics.It make full use of the image area information,build a energy model,and using variation gradient information to establish a global energy model to get the minimization value,which is geodesic active contour (GAC) model.Experimental results show that the method set in the initial outline of the evolution without success to avoid the reinitialization and correction process,thus saving computing time.With traditional methods and TV and CV method,the method convergence stable segmentation accuracy is good,easy parameter adjustment and split speed,better medical treatment of low contrast,blurred image.

关键词： Level Set Medical Image Segmentation GAC Global Minimum

作者: Yanming Pan Kejian Feng Dan Yang YuKuan Feng Yanwei Wang

作者单位: Department of Scientific Research Department of Anatomy Department of Foreign Languages Teaching Centre Mudanjiang Medical University Mudanjiang, Heilongjia College of Automation Harbin Engineering University Harbin, HeiLongjiang Province, China

会议类型: 国际会议

会议名称: 2013 ICME International Conference on Complex Medical Engineering(2013 ICME复合医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 429-432

在线出版日期: 2013-05-25（万方平台首次上网日期，不代表论文的发表时间）