摘要
针对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的不足,提出了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。应用该算法分别对临床100张肝脏图像和牙菌斑图像进行分割,结果显示了该算法的良好性能。
Interactive image segmentation methods usually ask users to mark much more initial seeds or more than one interaction when they are used for medical image segmentation with fuzzy boundaries. This paper presented an optimized interactive image segmentation algorithm with multi-threshold technology. Based on GorwCut algorithm put forward by Vladimir, the optimized algorithm introduced image gray histogram with more than one threshold values to generate initial seeds template automatically and then used improved cellular automaton iterative algorithm to realize image segmentation. The algorithm simplified the user interactive operations and improved the segmentation accuracy. In applications, the algorithm was used to test on 100 plaque and liver image segmentations respectively, of which the results show that the optimized algorithm is of good performance.
出处
《计算机应用》
CSCD
北大核心
2013年第5期1435-1438,1475,共5页
journal of Computer Applications
基金
国家自然科学基金资助项目(61074192)
北京科技大学冶金工程研究院基金资助项目(YJ2010-019)
江西省教育厅项目(GJJ11465)
关键词
交互
多阈值
灰度直方图
细胞自动机
医学图像分割
interaction
multi-threshold
gray histogram
cellular automata
medical image segmentation
作者简介
通信作者电子邮箱lanhong69@163．com兰红（1969-），女，辽宁鞍山人，博士研究生，主要研究方向：图像处理、模式识别；
闵乐泉（1951-），男，北京人，教授，博士生导师，主要研究方向：图像处理、混沌密码学、细胞神经网络。
