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基于最大流的交互式目标提取算法
引用本文:于丹,汤井田,徐大宏,罗东礼. 基于最大流的交互式目标提取算法[J]. 计算机工程与应用, 2007, 43(5): 246-248
作者姓名:于丹  汤井田  徐大宏  罗东礼
作者单位:中南大学,信息物理工程学院,生物医学工程研究所,长沙,410083
摘    要:医学图像处理中,目标提取在准确区分组织结构中起了重要的作用,论文介绍了基于最大流的交互式的目标提取算法,该方法把基于区域和基于边界方法结合起来,并用分水岭算法对图像做预分割,在其所分的区域上计算能量函数,然后最小化能量函数求最优边界。笔者结合自己研究的课题,针对目标标记步骤中聚类种子F和#色彩值的k-means算法进行改进,并把改进算法应用到人体器官切片目标分割中。

关 键 词:目标提取  最大流  图切割
文章编号:1002-8331(2007)05-0246-03
修稿时间:2006-06-01

Iteractive object extraction based on Max-flow
YU Dan,TANG Jing-tian,XU Da-hong,LUO Dong-li. Iteractive object extraction based on Max-flow[J]. Computer Engineering and Applications, 2007, 43(5): 246-248
Authors:YU Dan  TANG Jing-tian  XU Da-hong  LUO Dong-li
Affiliation:Institute of Biomedical Engineering,School of Info-Physics Geomatics Engineering,CSU,Changsha 410083,China
Abstract:Object extraction plays an important role in distinguishing organize framework accurately in medical image process.This text has introduced an interactive object extraction on the basis of max-flow,this method combines the basis of area with the basis of border method,and using watershed algorithm for image pre-segmentation,then calculating energy function on the segmented regions from it.The author uses one's own subject for research,applies this kind of algorithm to the human organ segmentation and improves in the k-means method by which the colors in seeds F and β are clustered in object marking.
Keywords:object extraction    Max-flow    graph cut
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