Medical image segmentation with improved gradient vector flow

被引:0
|
作者
Cheng, Jinyong [1 ]
Sun, Xiaoyun [1 ]
机构
[1] School of Information, Shandong Provincial Key Laboratory of Fine Chemicals, Shandong Polytechnic University, Jinan, 250353, China
关键词
Image enhancement - Brain mapping - Image segmentation;
D O I
暂无
中图分类号
学科分类号
摘要
In this study, we discover some deficiencies of GVF and GGVF Snake such as it can not capture boundaries like U and Ω completely because of the counteraction of some external forces and the influence of the local minimum external forces. Based on analyzing force distribution rules of gradient vector flow, a standard is introduced to distinguish every control point is true or false. An additional control force is added to GVF Snake model. The direction of control force is gained by tracking the force field and the motion of snake control points. Experimentation proves that the new GVF Snake model can solve the problem that GVF and GGVF Snake model can not detect the boundaries like U and Ω and the new algorithm can improve GVF snake model's ability to capture thin boundary indentation like the boundary of brain image. © Maxwell Scientific Organization, 2012.
引用
收藏
页码:3951 / 3957
相关论文
共 50 条
  • [31] A Gradient Vector Flow Snake Model using Novel Coefficients Setting for Infrared Image Segmentation
    Zhang, Rui
    3RD INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE AND MECHANICAL ENGINEERING, (ICMSME 2016), 2016, : 142 - 146
  • [32] Variational Segmentation of Vector-Valued Images With Gradient Vector Flow
    Jaouen, Vincent
    Gonzalez, Paulo
    Stute, Simon
    Guilloteau, Denis
    Chalon, Sylvie
    Buvat, Irene
    Tauber, Clovis
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2014, 23 (11) : 4773 - 4785
  • [33] A simplified texture gradient method for improved image segmentation
    Qi Wang
    M. W. Spratling
    Signal, Image and Video Processing, 2016, 10 : 679 - 686
  • [34] A simplified texture gradient method for improved image segmentation
    Wang, Qi
    Spratling, M. W.
    SIGNAL IMAGE AND VIDEO PROCESSING, 2016, 10 (04) : 679 - 686
  • [35] An Improved Hybrid Model for Medical Image Segmentation
    Yang Feng
    Sun Xiaohuan
    Chen Guoyue
    Wen Tiexiang
    2008 11TH IEEE SINGAPORE INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS (ICCS), VOLS 1-3, 2008, : 367 - +
  • [36] Medical image segmentation using improved FCM
    Zhang XiaoFeng
    Zhang CaiMing
    Tang WenJing
    Wei ZhenWen
    SCIENCE CHINA-INFORMATION SCIENCES, 2012, 55 (05) : 1052 - 1061
  • [37] Medical image segmentation using improved FCM
    XiaoFeng Zhang
    CaiMing Zhang
    WenJing Tang
    ZhenWen Wei
    Science China Information Sciences, 2012, 55 : 1052 - 1061
  • [38] Medical image segmentation using improved FCM
    ZHANG XiaoFeng 1
    2 School of Information and Electrical Engineering
    3 School of Computer Science and Technology
    4 Shandong Province Key Lab of Digital Media Technology
    ScienceChina(InformationSciences), 2012, 55 (05) : 1052 - 1061
  • [39] Improved UNet with Attention for Medical Image Segmentation
    AL Qurri, Ahmed
    Almekkawy, Mohamed
    SENSORS, 2023, 23 (20)
  • [40] Gradient and Polynomial Approximation Methods for Medical Image Segmentation
    Piekar, Ewelina
    Momot, Aline
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2015, 5 (06) : 1337 - 1349