摘要
在由序列的二维轮廓线重构出面模型来表示三维形体的面绘制方式中,首先要解决相邻两层切片上的轮廓线之间的匹配连接关系。针对目前的轮廓线匹配算法容易导致错误匹配的问题,提出一种基于遗传算法的轮廓模糊匹配算法。模糊性为轮廓匹配问题本身所具有,借鉴遗传算法这一种全局优化自适应概率搜索算法,可以准确表达轮廓匹配中的约束,有效地减少错误匹配的发生。在肝脏的CT数据三维重建中应用该算法取得了比较理想的效果。
In the surface reconstruction from contour of paralleled serial slice, the first step is matching the contour on adjacent slice. It is easy to match error contour by existing algorithms, so a new method for contour matching over genetic algorithm is proposed in this paper. The fuzzy property is the character of contour matching and the genetic algorithm is a global optimizing adaptive search algorithm. With this algorithm, it is accurate to express the restriction of contour matching and to reduce the error matching effectively. This algorithm is applied to the reconstruction of 3-D CT for liver and the result is perfect.
出处
《系统仿真学报》
CAS
CSCD
2004年第4期772-774,共3页
Journal of System Simulation
基金
重庆市科技基金资助项目(2002cc23)
关键词
轮廓匹配
模式识别
模糊
遗传算法
contour matching
pattern recognize
fuzzy
genetic algorithm