%0 Journal Article
%T Segmentation of multiple sclerosis lesions based on D-S evidence theory<br>基于D-S证据理论的多发性硬化症病灶分割算法*
%A LI Bin
%A LIU Tong
%A <br>李彬
%A 刘同
%J 计算机应用研究
%D 2011
%I 
%X Multiple sclerosis (MS) is an inflammatory demyelinating disease that would damage central nervous system. There was a growing attention to the segmentation algorithms of MS lesions. This paper developed an automatic algorithm for MS lesions segmentation by utilizing the fusion T1 and T2-weighted MR brain images based on D-S evidence theory and FCM clustering algorithm. First, segmented T1 and T2-weighted MR brain images by a FCM clustering algorithm. Then fused the resultant images according to the joint mass of T1 and T2-weighted MR brain images to produce the segmentation of MS lesions. The testing experiments on MR brain images show that the proposed algorithm is able to improve the segmentation accuracy, which is important to assist the diagnosis of MS in clinic.
%K image segmentation
%K D-S evidence theory
%K fuzzy C-mean clustering
%K information fusion
%K multiple sclerosis lesions<br>图像分割
%K D-S证据理论
%K 模糊C-均值聚类
%K 信息融合
%K 多发性硬化症
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=ED157B6DE302FC7AF5063F4FF3F7AAF1&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=CA4FD0336C81A37A&sid=73648F51F187AC5E&eid=A7AE820C12CC9AD3&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=13