计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (7): 206-208.

• 工程与应用 • 上一篇    下一篇

基于两组细胞神经网络的工业CT图像分割

刘长江1,2,3,曾 理1,2   

  1. 1.重庆大学 光电技术及系统教育部重点实验室 ICT研究中心,重庆 400044
    2.重庆大学 数理学院,重庆 400044
    3.四川理工学院 数学系,四川 自贡 643000
  • 收稿日期:2007-10-18 修回日期:2008-01-07 出版日期:2008-03-01 发布日期:2008-03-01
  • 通讯作者: 刘长江

Industrial Computerized Tomography image segmentation based on two Cellular Neural Networks

LIU Chang-jiang1,2,3,ZENG Li1,2   

  1. 1.ICT Research Center,Key Laboratory of Optoelectronic Technology and System of the Education Ministry of China,Chongqing University,Chongqing 400044,China
    2.College of Mathematics and Physics,Chongqing University,Chongqing 400044,China
    3.Dept. of Mathematics,Sichuan University of Science & Engineering,Zigong,Sichuan 643000,China
  • Received:2007-10-18 Revised:2008-01-07 Online:2008-03-01 Published:2008-03-01
  • Contact: LIU Chang-jiang

摘要: 采用两组细胞神经网络实现工业CT图像的分割。一组细胞神经网络用粗分割,得到阈值分割图像,在此基础上用另一组细胞神经网络细分割,得到精细的边缘等信息。修正网络稳定态的定义,以网络伪稳定态作为网络迭代过程的终止条件。应用该方法,以发动机切片CT图像作为实验对象,能取得较好的效果。

Abstract: Two groups of Cellular Neural Networks(CNN) have been used to segment Industrial Computerized Tomography(ICT) Images.The first group,namely rough image segmentation,has been adopted to obtain thresholding images,then with the adaptation of the second group some more sophisticated segmentation information will be procured,with edges included.This article deals with the Pseudo-steady-state of net,which has been served as the termination condition of the iteration.Experimental results of engineering image series demonstrate the efficiency of the methods presented in the article.