%0 Journal Article
%T The Study of Automatic Classification for Ultrasound Placenta Images Based on Adaptive Multiple Neural Networks<br>基于自适应多神经网络的胎盘超声图像自动分级研究
%A MAO Jian-fei
%A YANG Xu-hua
%A TIAN Xian-zhong
%A <br>毛剑飞
%A 杨旭华
%A 田贤忠
%J 中国图象图形学报
%D 2006
%I 
%X To solve the problem of automatic classification for ultrasound placenta images, we put forward an algorithm based on adaptive multiple neural networks. Two layers of BP net models were designed to carry Two-Stage separation of the placenta in this algorithm other than general one stage separation algorithm. When training networks, we do not adopt the common method which rounds the output of the networks, but propose a more reasonable grading rule, then present an adaptive threshold-gotten method to determine the reasonable placenta level. Experiments and clinic applications indicate that the similar classification result can be gotten by our algorithm as by experts, and the classification result by the algorithm before threshold division can give the doctor a good reference on the precise measurement of the placenta maturity, thereby, it has a good future in clinic applications.
%K ultrasound placenta images
%K automatic classification
%K adaptive multiple neural networks
%K threshold division
%K two-stage separation<br>胎盘超声图像
%K 自动分级
%K 自适应多神经网络
%K 阈值分割
%K 两级分离
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=8982E922948CD800&yid=37904DC365DD7266&vid=708DD6B15D2464E8&iid=DF92D298D3FF1E6E&sid=78AF84DBB4041008&eid=714E16F7CF56F343&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=12