Medical Image Segmentation Based on Immune Clonal Optimization

摘要：

Based on the clonal selection theory of Artificial Immune System, a novel optimal entropy threshold medical image segmentation method is proposed, in which, the affinity function is the optimal entropy threshold, and the medical image segmentation is considered as a optimization problem, clonal operator effectively enlarges searching range, supplies the diversity of solutions and can find the optimal threshold. This paper applies new algorithm to the challenging application: gray matter/white matter segmentation in MRI images, the algorithm is depicted in detail and the convergence is proven, the performance and computational complexity of the algorithm are described by quantitative analysis. Experiment results demonstrate the potential of the algorithm for medical image segmentation.

关键词： optimal entropy threshold medical image segmentation artificial immune system clonal selection theory

作者: Wenping Ma Licheng Jiao Ronghua Shang Fujia Zhao

作者单位: Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China,Institute of Intelligent Information Processing,Xidian University,Xian 710071,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 377-381

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）