CFP last date
22 April 2024
Reseach Article

Integrating Variational Level Set Method and Fuzzy c-Means to Automatically Segment the MRI Brain Images

by Pratibha Singh, H. S. Bhadauria, Annapurna Bhadauria
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 96 - Number 14
Year of Publication: 2014
Authors: Pratibha Singh, H. S. Bhadauria, Annapurna Bhadauria
10.5120/16861-6745

Pratibha Singh, H. S. Bhadauria, Annapurna Bhadauria . Integrating Variational Level Set Method and Fuzzy c-Means to Automatically Segment the MRI Brain Images. International Journal of Computer Applications. 96, 14 ( June 2014), 11-13. DOI=10.5120/16861-6745

@article{ 10.5120/16861-6745,
author = { Pratibha Singh, H. S. Bhadauria, Annapurna Bhadauria },
title = { Integrating Variational Level Set Method and Fuzzy c-Means to Automatically Segment the MRI Brain Images },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 96 },
number = { 14 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 11-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume96/number14/16861-6745/ },
doi = { 10.5120/16861-6745 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:21:44.269718+05:30
%A Pratibha Singh
%A H. S. Bhadauria
%A Annapurna Bhadauria
%T Integrating Variational Level Set Method and Fuzzy c-Means to Automatically Segment the MRI Brain Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 96
%N 14
%P 11-13
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The main aim of this paper is to provide a method that could easily delineate the exact location of tumor region from brain MRI images by integrating the fuzzy c-means and level set method. The proposed method smoothly exploits the spatial function during FCM clustering which in turn proves the automaticity of the method by dividing the original image into clusters and then using one cluster for automatic initialization. Since automating the process reduces the time utilization of processing thereby making the work less tedious, hence if considered it could be competent tool in future. Another problem associated when utilizing manual methods is that it may lead to different results when produced by different medical experts which can be completely erased while using this method. Secondly, the proposed method uses the level set method to find the contour of tumor region in the original image which helps in situations where image changes their topologies by merging or splitting in two. Thus, the proposed method is using the convenient variational level set method in place of traditional level set method thereby eliminating one more drawback of re-initializing the contour several times during image segmentation.

References
  1. Keh-Shih Chuang , Hong-Long Tzeng , Sharon Chen , Jay Wu ,Tzong-Jer Chen, Fuzzy c-means clustering with spatial information for image segmentation, September,6, 2005.
  2. Z. M. Wang, Y. C. Soh, Q. Song, and K. Sim, "Adaptive spatial information-theoretic clustering for image segmentation,", vol. 42, no. 9, pp. 2029–2044, 2009
  3. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active contour models," Int. J. Comput. Vis. , vol. 1, pp. 321–331,1987.
  4. S. Osher and J. Sethian, "Fronts propagating with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulations," J. Comp. Phys. , vol. 79, pp. 12-49, 1988.
  5. Tsai, Y. -H. R. , Cheng, L. -T. , Osher, S. , Zhao, H. -K. : Fast sweeping algorithms for a class of Hamilton-Jacobi equations. SIAM J. Numer. Anal. 41, 673–694 (2003).
  6. S. Osher and R. P. Fedkiw. Level set methods and dynamic implicit surfaces. Springer, 2003.
  7. Chunming Li , Chenyang Xu , Changfeng Gui , and Martin D. Fox , "Level Set Evolution Without Re-initialization: A New Variational Formulation", Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) 1063-6919/05 $20. 00 © 2005 IEEE.
  8. Yang MS, Hu YJ, Lin KCR, Lin CCL. Segmentation techniques fortissue differentiation in MRI of Ophthalmology using fuzzy clustering algorithms. Magn Reson Imaging 2002;20:173–9.
  9. J. A. Sethian, Level set methods and fast marching methods,Cambridge: Cambridge University Press, 1999.
  10. B. Vemuri and Y. Chen, "Joint image registration and segmentation",Geometric Level Set Methods in Imaging, Vision, and Graphics, Springer, pp. 251-269, 2003.
Index Terms

Computer Science
Information Sciences

Keywords

Image segmentation level set methods Fuzzy c-means defuzzification variational level sets.