%0 Journal Article
%T A Brain MR Images De-bias Model Based on Genetics Algorithm<br>一种基于遗传算法的脑MR图像去偏移场模型
%A WANG Li
%A CHEN Yun-jie
%A TANG Yang
%A WEI Zhi-hui
%A HENG Pheng-ann
%A XIA De-shen
%A <br>王利
%A 陈允杰
%A 汤杨
%A 韦志辉
%A 王平安
%A 夏德深
%J 中国图象图形学报
%D 2008
%I 
%X Intrascan intensity inhomogeneities are a common source of difficulty for MRI segmentation.We estimate the bias field by Legendre polynomials.The bias field could be the best when we get minimum entropy.It needs to work out parameters of the base function in the process of finding bias field,but conventional methods such as gradient-descent method often find local best.To find global best,we present genetics algorithm to find best parameters to estimate the bias field,however the result was not satisfying.Then we make some modification of genetics algorithm to make it easier to find global best.Experiments on the segmentation of brain magnetic resonance images show our modification can achieve optimal bias field and accurate segmentation results.
%K magnetic resonance image(MRI)
%K bias field
%K entropy
%K gradient-descent
%K genetics algorithm
%K local best
%K global best<br>磁共振图像
%K 偏移场
%K 信息熵
%K 梯度下降法
%K 遗传算法
%K 局部最优
%K 全局最优
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=C88B5C03FDC069625080F3E93522643A&yid=67289AFF6305E306&vid=FC0714F8D2EB605D&iid=DF92D298D3FF1E6E&sid=4CBFE0C7AFFA0387&eid=F7C51083F4D893E5&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=21