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
相关论文
共 50 条
  • [21] Hybrid Masked Image Modeling for 3D Medical Image Segmentation
    Xing, Zhaohu
    Zhu, Lei
    Yu, Lequan
    Xing, Zhiheng
    Wan, Liang
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2024, 28 (04) : 2115 - 2125
  • [22] Rough Set Theory based segmentation of color images
    Mohabey, Akash
    Ray, A.K.
    [J]. Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, 2000, : 338 - 342
  • [23] Rough set theory based segmentation of color images
    Mohabey, A
    Ray, AK
    [J]. PEACHFUZZ 2000 : 19TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, 2000, : 338 - 342
  • [24] Masked image modeling-based boundary reconstruction for 3D medical image segmentation
    Liu, Chang
    Cheng, Yuanzhi
    Tamura, Shinichi
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 166
  • [25] Medical image segmentation using rough set and local polynomial regression
    Cong-Hua Xie
    Yong-Jun Liu
    Jin-Yi Chang
    [J]. Multimedia Tools and Applications, 2015, 74 : 1885 - 1914
  • [26] Medical image segmentation using rough set and local polynomial regression
    Xie, Cong-Hua
    Liu, Yong-Jun
    Chang, Jin-Yi
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2015, 74 (06) : 1885 - 1914
  • [27] Combining interpolation and 3D level set method (I+3DLSM) for medical image segmentation
    Doshi, T.
    Di Caterina, G.
    Soraghan, J.
    Petropoulakis, L.
    Grose, D.
    MacKenzie, K.
    Wilson, C.
    [J]. ELECTRONICS LETTERS, 2016, 52 (08) : 592 - 593
  • [28] Active Volume Models for 3D Medical Image Segmentation
    Shen, Tian
    Li, Hongsheng
    Qian, Zhen
    Huang, Xiaolei
    [J]. CVPR: 2009 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-4, 2009, : 707 - +
  • [29] Elastic Boundary Projection for 3D Medical Image Segmentation
    Ni, Tianwei
    Xie, Lingxi
    Zheng, Huangjie
    Fishman, Elliot K.
    Yuille, Alan L.
    [J]. 2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 2104 - 2113
  • [30] Volumetric Attention for 3D Medical Image Segmentation and Detection
    Wang, Xudong
    Han, Shizhong
    Chen, Yunqiang
    Gao, Dashan
    Vasconcelos, Nuno
    [J]. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2019, PT VI, 2019, 11769 : 175 - 184
12345