About this Journal Submit a Manuscript Table of Contents
Journal of Biomedicine and Biotechnology
Volume 2009 (2009), Article ID 717102, 12 pages
http://dx.doi.org/10.1155/2009/717102
Research Article

An Evaluation of Cellular Neural Networks for the Automatic Identification of Cephalometric Landmarks on Digital Images

1Istituto di II Clinica Odontoiatrica, Policlinico Città Universitaria, Via S. Sofia 78, 95123 Catania, Italy
2Dipartimento di Ingegneria Informatica e Telecomunicazioni, Università di Catania, Viale A. Doria 6, 95125 Catania, Italy

Received 16 February 2009; Revised 16 May 2009; Accepted 18 June 2009

Academic Editor: Rita Casadio

Copyright © 2009 Rosalia Leonardi 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. B. H. Broadbent, “A new X-ray technique and its application to orthodontia,” Angle Orthodontist, vol. 1, pp. 45–66, 1931.
  2. S. Baumrind and D. M. Miller, “Computer-aided head film analysis: the University of California San Francisco method,” American Journal of Orthodontics, vol. 78, no. 1, pp. 41–65, 1980.
  3. D. B. Forsyth, W. C. Shaw, S. Richmond, and C. T. Roberts, “Digital imaging of cephalometric radiographs—part 2: image quality,” Angle Orthodontist, vol. 66, no. 1, pp. 43–50, 1996.
  4. R. Leonardi, D. Giordano, F. Maiorana, and C. Spampinato, “Automatic cephalometric analysis: a systematic review,” Angle Orthodontist, vol. 78, no. 1, pp. 145–151, 2008. View at Publisher · View at Google Scholar · View at PubMed
  5. T. J. Hutton, S. Cunningham, and P. Hammond, “An evaluation of active shape models for the automatic identification of cephalometric landmarks,” European Journal of Orthodontics, vol. 22, no. 5, pp. 499–508, 2000.
  6. W. Yue, D. Yin, C. Li, G. Wang, and T. Xu, “Automated 2-D cephalometric analysis on X-ray images by a model-based approach,” IEEE Transactions on Biomedical Engineering, vol. 53, no. 8, pp. 1615–1623, 2006. View at Publisher · View at Google Scholar · View at PubMed
  7. A. D. Lévy-Mandel, A. N. Venetsanopoulos, and J. K. Tsotsos, “Knowledge-based landmarking of cephalograms,” Computers and Biomedical Research, vol. 19, no. 3, pp. 282–309, 1986.
  8. S. Parthasarathy, S. T. Nugent, P. G. Gregson, and D. F. Fay, “Automatic landmarking of cephalograms,” Computers and Biomedical Research, vol. 22, no. 3, pp. 248–269, 1989.
  9. D. B. Forsyth and D. N. Davis, “Assessment of an automated cephalometric analysis system,” European Journal of Orthodontics, vol. 18, no. 5, pp. 471–478, 1996.
  10. B. Romaniuk, M. Desvignes, M. Revenu, and M.-J. Deshayes, “Shape variability and spatial relationships modeling in statistical pattern recognition,” Pattern Recognition Letters, vol. 25, no. 2, pp. 239–247, 2004. View at Publisher · View at Google Scholar
  11. D. J. Rudolph, P. M. Sinclair, and J. M. Coggins, “Automatic computerized radiographic identification of cephalometric landmarks,” American Journal of Orthodontics and Dentofacial Orthopedics, vol. 113, no. 2, pp. 173–179, 1998.
  12. Y.-T. Chen, K.-S. Cheng, and J.-K. Liu, “Improving cephalogram analysis through feature subimage extraction,” IEEE Engineering in Medicine and Biology Magazine, vol. 18, no. 1, pp. 25–31, 1999. View at Publisher · View at Google Scholar
  13. J. Cardillo and M. A. Sid-Ahmed, “An image processing system for locating craniofacial landmarks,” IEEE Transactions on Medical Imaging, vol. 13, no. 2, pp. 275–289, 1994. View at Publisher · View at Google Scholar · View at PubMed
  14. V. Ciesielski, A. Innes, J. Sabu, and J. Mamutil, “Genetic programming for landmark detection in cephalometric radiology images,” International Journal of Knowledge-Based and Intelligent Engineering Systems, vol. 7, pp. 164–171, 2003.
  15. S. Sanei, P. Sanaei, and M. Zahabsaniei, “Cephalogram analysis applying template matching and fuzzy logic,” Image and Vision Computing, vol. 18, no. 1, pp. 39–48, 1999. View at Publisher · View at Google Scholar
  16. I. El-Feghi, M. A. Sid-Ahmed, and M. Ahmadi, “Automatic localization of craniofacial landmarks for assisted cephalometry,” Pattern Recognition, vol. 37, no. 3, pp. 609–621, 2004. View at Publisher · View at Google Scholar
  17. J.-K. Liu, Y.-T. Chen, and K.-S. Cheng, “Accuracy of computerized automatic identification of cephalometric landmarks,” American Journal of Orthodontics and Dentofacial Orthopedics, vol. 118, no. 5, pp. 535–540, 2000. View at Publisher · View at Google Scholar · View at PubMed
  18. V. Grau, M. Alcañiz, M. C. Juan, C. Monserrat, and C. Knoll, “Automatic localization of cephalometric landmarks,” Journal of Biomedical Informatics, vol. 34, no. 3, pp. 146–156, 2001. View at Publisher · View at Google Scholar · View at PubMed
  19. J. Yang, X. Ling, Y. Lu, M. Wei, and G. Deng, “Cephalometric image analysis and measurement for orthognatic surgery,” Medical and Biological Engineering and Computing, vol. 39, pp. 279–284, 2001.
  20. T. Stamm, H. A. Brinkhaus, U. Ehmer, N. Meier, and F. Bollmann, “Computer-aided automated landmarking of cephalograms,” Journal of Orofacial Orthopedics, vol. 59, no. 2, pp. 73–81, 1998.
  21. D. Giordano, R. Leonardi, F. Maiorana, G. Cristaldi, and M. L. Distefano, “Automatic landmarking of cephalograms by cellular neural networks,” in Proceedings of the 10th Conference on Artificial Intelligence in Medicine (AIME '05), vol. 3581 of Lecture Notes in Computer Science, pp. 333–342, Aberdeen, Scotland, July 2005.
  22. D. Giordano, R. Leonardi, F. Maiorana, and C. Spampinato, “Cellular neural networks and dynamic enhancement for cephalometric landmarks detection,” in Proceedings of the 8th International Conference on Artificial Intelligence and Soft Computing (ICAISC '06), vol. 4029 of Lecture Notes in Computer Science, pp. 768–777, Zakopane, Poland, June 2006. View at Publisher · View at Google Scholar
  23. L. Q. Bruntz, J. M. Palomo, S. Baden, and M. G. Hans, “A comparison of scanned lateral cephalograms with corresponding original radiographs,” American Journal of Orthodontics and Dentofacial Orthopedics, vol. 130, no. 3, pp. 340–348, 2006. View at Publisher · View at Google Scholar · View at PubMed
  24. R. K. W. Schulze, M. B. Gloede, and G. M. Doll, “Landmark identification on direct digital versus film-based cephalometric radiographs: a human skull study,” American Journal of Orthodontics and Dentofacial Orthopedics, vol. 122, no. 6, pp. 635–642, 2002. View at Publisher · View at Google Scholar · View at PubMed
  25. M. Santoro, K. Jarjoura, and T. J. Cangialosi, “Accuracy of digital and analogue cephalometric measurements assessed with the sandwich technique,” American Journal of Orthodontics and Dentofacial Orthopedics, vol. 129, no. 3, pp. 345–351, 2006. View at Publisher · View at Google Scholar · View at PubMed
  26. L. O. Chua and T. Roska, “The CNN paradigm,” IEEE Transactions on Circuits and Systems I, vol. 40, no. 3, pp. 147–156, 1993. View at Publisher · View at Google Scholar
  27. T. Roska, L. Kek, L. Nemes, A. Zarandy, and P. Szolgay, CSL CNN Software Library (Templates and Algorithms), Budapest, Hungary, 1999.
  28. I. Aizenberg, N. Aizenberg, J. Hiltner, C. Moraga, and E. Meyer Zu Bexten, “Cellular neural networks and computational intelligence in medical image processing,” Image and Vision Computing, vol. 19, no. 4, pp. 177–183, 2001. View at Publisher · View at Google Scholar
  29. T. Yang, Handbook of CNN Image Processing, Yang's Scientific Research Institute LLC, 2002.
  30. T. Szabo, P. Barsi, and P. Szolgay, “Application of analogic CNN algorithms in telemedical neuroradiology,” in Proceedings of the 7th IEEE International Workshop on Cellular Neural Networks and Their Applications (CNNA '02), pp. 579–586, 2002.
  31. A. Gacsádi, C. Grava, and A. Grava, “Medical image enhancement by using cellular neural networks,” Computers in Cardiology, vol. 32, pp. 821–824, 2005. View at Publisher · View at Google Scholar
  32. D. Giordano and F. Maiorana, “A grid implementation of a cellular neural network simulator,” in Proceedings of the 16th IEEE International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE '07), pp. 241–246, Paris, France, 2007. View at Publisher · View at Google Scholar
  33. W. Geelen, A. Wenzel, E. Gotfredsen, M. Kruger, and L.-G. Hansson, “Reproducibility of cephalometric landmarks on conventional film, hardcopy, and monitor-displayed images obtained by the storage phosphor technique,” European Journal of Orthodontics, vol. 20, no. 3, pp. 331–340, 1998.
  34. Y.-J. Chen, S.-K. Chen, J. C.-C. Yao, and H.-F. Chang, “The effects of differences in landmark identification on the cephalometric measurements in traditional versus digitized cephalometry,” Angle Orthodontist, vol. 74, no. 2, pp. 155–161, 2004.
  35. B. Trpkova, P. Major, N. Prasad, and B. Nebbe, “Cephalometric landmarks identification and reproducibility: a meta analysis,” American Journal of Orthodontics and Dentofacial Orthopedics, vol. 112, no. 2, pp. 165–170, 1997.