摘要
交互式图像分割方法对边界模糊的医学图像进行分割时通常需要用户标记较多的初始种子或进行二次交互,这给用户带来不便。针对此问题,提出一种简化标记的多阈值优化交互式分割算法,该算法在GrowCut交互式算法基础上通过引入图像灰度直方图的多个阈值自动生成初始种子模板,并利用改进的细胞自动机迭代算法实现图像分割。算法简化了用户操作,提高了分割精度。算法应用于临床肝脏图像和牙菌斑图像分割,显示了良好的分割效果。
Interactive image segmentation methods usually require users to provide much more initial seeds or more than once interactive when they are used for medical image segmentation with fuzzy boundaries. This paper presented an op timized interactive image segraentation algorithm with multi-thresholds technology. The proposed algorithm is based on GorwCut algorithm and improved in two aspects： one is automatically generating initial seeds templates by image gray histogram with multi-thresholds, and the other is raising iterative efficiency by improved cellular automaton iterative al- gorithm. Compared with GrowCut algorithm, the proposed algorithm simplifies the user interactive operations and im- proves the segmentation accuracy. Experimental results on clinical plaque and liver image segmentations demostrate the sound performances of the proposed algorithm.
出处
《计算机科学》
CSCD
北大核心
2013年第9期296-299,共4页
Computer Science
基金
江西省教育厅科技项目(GJJ11465)资助
关键词
交互式
多阈值
灰度直方图
细胞自动机
医学图像分割
Interactive, Multi-thresholds, Histogram, Cellular automata, Medical image segmentation
作者简介
兰红（1969-），女，博士生，副教授，主要研究方向为图像处理、模式识别，E-mail：lanhong69@163．com
