Table of Contents Author Guidelines Submit a Manuscript
Computational and Mathematical Methods in Medicine
Volume 2015, Article ID 710326, 14 pages
http://dx.doi.org/10.1155/2015/710326
Research Article

Segmentation of Regions of Interest Using Active Contours with SPF Function

1Department of Computer Engineering and Mathematics, Rovira i Virgili University, 43007 Tarragona, Spain
2Department of Computer Science & Engineering, Chung-Ang University, Seoul 156-756, Republic of Korea
3Korea Institute of Science & Technology Information, Daejeon 305-806, Republic of Korea

Received 16 October 2014; Revised 10 January 2015; Accepted 31 January 2015

Academic Editor: Tianye Niu

Copyright © 2015 Farhan Akram et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. R. Acharya, R. Wasserman, J. Stevens, and C. Hinojosa, “Biomedical imaging modalities: a tutorial,” Computerized Medical Imaging & Graphics, vol. 19, no. 1, pp. 3–25, 1995. View at Publisher · View at Google Scholar · View at Scopus
  2. B.-W. Hong and B.-S. Sohn, “Segmentation of regions of interest in mammograms in a topographic approach,” IEEE Transactions on Information Technology in Biomedicine, vol. 14, no. 1, pp. 129–139, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. A. P. M. Forrest and R. J. Aitken, “Mammography screening for breast cancer,” Annual Review of Medicine, vol. 41, pp. 117–132, 1990. View at Publisher · View at Google Scholar · View at Scopus
  4. S. M. Astley, C. R. M. Boggis, K. Walker et al., “An evaluation of a commercial prompting system in a busy screening centre,” in Digital Mammography: IWDM 2002—6th International Workshop on Digital Mammography, pp. 471–475, Springer, Berlin, Germany, 2003. View at Publisher · View at Google Scholar
  5. S. M. Astley, R. Zwiggelaar, C. Wolstenholme, and C. J. Taylor, “Prompting in mammography: how accurate must prompt generators be?” in Proceedings of the 4th International Workshop on Digital Mammography, pp. 347–354, 1998.
  6. Z. Huo, M. L. Giger, and C. J. Vyborny, “Computerized analysis of multiple-mammographic views: potential usefulness of special view mammograms in computer-aided diagnosis,” IEEE Transactions on Medical Imaging, vol. 20, no. 12, pp. 1285–1292, 2001. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: active contour models,” International Journal of Computer Vision, vol. 1, no. 4, pp. 321–331, 1988. View at Publisher · View at Google Scholar · View at Scopus
  8. V. Caselles, R. Kimmel, and G. Sapiro, “Geodesic active contours,” International Journal of Computer Vision, vol. 22, no. 1, pp. 61–79, 1997. View at Publisher · View at Google Scholar · View at Scopus
  9. C. Li, C. Xu, C. Gui, and M. D. Fox, “Level set evolution without re-initialization: a new variational formulation,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '05), pp. 430–436, San Diego, Calif, USA, June 2005. View at Scopus
  10. N. Paragios and R. Deriche, “Geodesic active regions and level set methods for supervised texture segmentation,” International Journal of Computer Vision, vol. 46, no. 3, pp. 223–247, 2002. View at Publisher · View at Google Scholar · View at Scopus
  11. T. F. Chan and L. A. Vese, “Active contours without edges,” IEEE Transactions on Image Processing, vol. 10, no. 2, pp. 266–277, 2001. View at Publisher · View at Google Scholar · View at Scopus
  12. K. Zhang, L. Zhang, H. Song, and W. Zhou, “Active contours with selective local or global segmentation: a new formulation and level set method,” Image and Vision Computing, vol. 28, no. 4, pp. 668–676, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. D. Mumford and J. Shah, “Optimal approximations by piecewise smooth functions and associated variational problems,” Communications on Pure and Applied Mathematics, vol. 42, no. 5, pp. 577–685, 1989. View at Publisher · View at Google Scholar · View at MathSciNet
  14. J. Lie, M. Lysaker, and X.-C. Tai, “A binary level set model and some applications to Mumford-Shah image segmentation,” IEEE Transactions on Image Processing, vol. 15, no. 5, pp. 1171–1181, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. L. A. Vese and T. F. Chan, “A multiphase level set framework for image segmentation using the Mumford and Shah model,” International Journal of Computer Vision, vol. 50, no. 3, pp. 271–293, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. D. Cremers, “A multiphase level set framework for motion segmentation,” in Scale Space Methods in Computer Vision: 4th International Conference, Scale Space 2003 Isle of Skye, UK, June 10–12, 2003 Proceedings, vol. 2695 of Lecture Notes in Computer Science, pp. 599–614, Springer, Berlin, Germany, 2003. View at Publisher · View at Google Scholar
  17. R. Ronfard, “Region-based strategies for active contour models,” International Journal of Computer Vision, vol. 13, no. 2, pp. 229–251, 1994. View at Publisher · View at Google Scholar · View at Scopus
  18. C. Li, C.-Y. Kao, J. C. Gore, and Z. Ding, “Implicit active contours driven by local binary fitting energy,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '07), pp. 1–7, Washington, DC, USA, June 2007. View at Publisher · View at Google Scholar · View at Scopus
  19. H. Jiang, R. Feng, and X. Gao, “Level set based on signed pressure force function and its application in liver image segmentation,” Wuhan University Journal of Natural Sciences, vol. 16, no. 3, pp. 265–270, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. J. Gomes and O. Faugeras, “Reconciling distance functions and level sets,” Journal of Visual Communication and Image Representation, vol. 11, no. 2, pp. 209–223, 2000. View at Publisher · View at Google Scholar · View at Scopus
  21. L. C. Evans, Partial Differential Equations , Graduate Studies in Mathematics, vol. 19, American Mathematical Society, Providence, RI, USA, 1998.
  22. C. Xu, A. Yezzi Jr., and J. L. Prince, “On the relationship between parametric and geometric active contours,” in Proceedings of the 34th Asilomar Conference on Signals, Systems and Computers, pp. 483–489, November 2000. View at Scopus
  23. F. Akram, J. H. Kim, and K. N. Choi, “Active contour method with locally computed signed pressure force function: an application to brain MR image segmentation,” in Proceedings of the 7th International Conference on Image and Graphics (ICIG '13), pp. 154–159, July 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. F. Akram, J. H. Kim, H. U. Lim, and K. N. Choi, “Segmentation of intensity inhomogeneous brain MR images using active contours,” Computational and Mathematical Methods in Medicine, vol. 2014, Article ID 194614, 14 pages, 2014. View at Publisher · View at Google Scholar
  25. H. Carr, J. Snoeyink, and U. Axen, “Computing contour trees in all dimensions,” Computational Geometry, vol. 24, no. 2, pp. 75–94, 2003. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  26. The mini-MIAS database of mammograms, 2003, http://peipa.essex.ac.uk/info/mias.html.