3D Medical Image Segmentation Based on Rough Set Theory

被引：0
|
作者：
CHEN Shi-hao
机构：
来源：
Chinese Journal of Biomedical Engineering | 2007年 / 01期
关键词：
3D medical image; Segmentation; Rough set;
D O I：
暂无
中图分类号：
TP391.41 [];
学科分类号：
080203 ;
摘要：
This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI(region of interest) when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions: positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.
引用
收藏
页码：39 / 46
页数：8
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