%0 Journal Article
%T Improved fast medical image segmentation method<br>一种改进的快速医学图像分割方法*
%A LI Kang shun
%A WANG Chao liang
%A WANG Feng
%A <br>李康顺
%A 王超梁
%A 王峰
%J 计算机应用研究
%D 2012
%I 
%X In order to determine the best histogram entropy of medical image, this paper proposed a fast segmentation method based on improved evolutionary algorithm which could adjust the crossover and mutation possibility adaptively. It ensured the population diversity and overcame the local optimal and fast convergence of traditional evolutionary algorithm. The best thre shold searched was not only more stability but also greatly reduced searching time, and rapidly implemented medical image segmentation, moreover, the image after segmentation had a strong readability. Experimental results show that the method is faster and has a better segmentation effect.
%K medical image segmentation
%K histogram
%K evolutionary algorithm
%K entropy
%K threshold<br>医学图像分割
%K 直方图
%K 演化算法
%K 熵
%K 阈值
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=B42EDD6608FE925A51FFE1930D27B8DC&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=0B39A22176CE99FB&sid=231F9A307C169827&eid=34A7AB0452E6AF23&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=12