3D Medical Image Segmentation Based on Rough Set Theory
CHEN Shi-hao
TIAN Yun
WANG Yi
HAO Chong-yang
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.
机标关键词：Rough Set Theorymedical image segmentationrough set theoryexpert knowledge
分类号：TP391.4(计算技术、计算机技术)
资助基金：PH. D Site from Chinese Educational Department(20040699015)
论文发表日期：2007-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：8( 39-46 )
英文信息