%0 Journal Article
%T Improved coupled model for MR images segmentation and bias restoration<br>改进的核磁共振图像分割与偏移场恢复耦合模型
%A Wang Shunfeng
%A Ji Xiaon
%A Zhang Jianwei
%A Chen Yunjie
%A Fang Lin
%A Zhan Tianming
%A <br>王顺凤
%A 冀晓娜
%A 张建伟
%A 陈允杰
%A 方林
%A 詹天明
%J 中国图象图形学报
%D 2012
%I 
%X Medical image analysis is helpful for doctors to diagnose diseases. However, the images usually have noise and intensity inhomogeneities, which makes it hard to obtain satisfactory results using the traditional image segmentation methods. To solve these problems, we propose a coupled model based on local image information, which can segment images while restoring the bias field. In order to obtain global optimal results accurately and quickly, we improved the coupled model to be a convex function and solved it based on the Split-Bregman method. The experimental results show that our method can reduce the effect of the noise and intensity inhomogeneities, and obtain more accurate segmentation results while estimating the bias field efficiently.
%K magnetic resonance imaging
%K bias restoration
%K global convex segmentation
%K level set method
%K Split-Bregman method<br>磁共振成像
%K 偏移场恢复
%K 全局凸分割
%K 水平集方法
%K Split-Bregman方法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=0B63987600F2A39C9453E14E9AF1E7E6&yid=99E9153A83D4CB11&vid=BCA2697F357F2001&iid=9CF7A0430CBB2DFD&sid=C9B4EBB1C6A169D8&eid=334C32317477C964&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=10