Table of Contents Author Guidelines Submit a Manuscript
International Journal of Biomedical Imaging
Volume 2014, Article ID 518414, 13 pages
http://dx.doi.org/10.1155/2014/518414
Research Article

Despeckle Filtering for Multiscale Amplitude-Modulation Frequency-Modulation (AM-FM) Texture Analysis of Ultrasound Images of the Intima-Media Complex

1Departement of Computer Science, School of Sciences, Intercollege, 92 Ayias Phylaxeos Street, P. O. Box 51604, CY-3507 Limassol, Cyprus
2Departement of Electrical Engineering, Universidad de Ingenieria y Tecnologia, 2221 Lima, Peru
3Departement of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM 87131, USA
4Cyprus Institute of Neurology and Genetics, 1683 Nicosia, Cyprus
5The Vascular Screening and Diagnostic Centre, 1080 Nicosia, Cyprus
6Departement of Computer Science, University of Cyprus, 1678 Nicosia, Cyprus

Received 1 December 2013; Accepted 31 January 2014; Published 9 March 2014

Academic Editor: Tiange Zhuang

Copyright © 2014 C. P. Loizou 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. American Heart Association, Heart Disease and Stroke Statistics, Update, Dallas, Tex, USA, 2011.
  2. P. Pignoli, E. Tremoli, and A. Poli, “Intimal plus medial thickness of the arterial wall: a direct measurement with ultrasound imaging,” Circulation, vol. 74, no. 6, pp. 1399–1406, 1986. View at Google Scholar · View at Scopus
  3. L. E. Chambless, A. R. Folsom, L. X. Clegg et al., “Carotid wall thickness is predictive of incident clinical stroke: the Atherosclerosis Risk in Communities (ARIC) study,” American Journal of Epidemiology, vol. 151, no. 5, pp. 478–487, 2000. View at Google Scholar · View at Scopus
  4. C. P. Loizou, C. S. Pattichis, A. N. Nicolaides, and M. Pantziaris, “Manual and automated media and intima thickness measurements of the common carotid artery,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 56, no. 5, pp. 983–994, 2009. View at Publisher · View at Google Scholar · View at Scopus
  5. C. P. Loizou, M. Pantziaris, M. S. Pattichis, E. Kyriacou, and C. S. Pattichis, “Ultrasound image texture analysis of the intima and media layers of the common carotid artery and its correlation with age and gender,” Computerized Medical Imaging and Graphics, vol. 33, no. 4, pp. 317–324, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. R. F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, “Statistics of speckle in ultrasound B-scans,” IEEE Transactions on Sonics and Ultrasonics, vol. 30, no. 3, pp. 156–163, 1983. View at Google Scholar · View at Scopus
  7. Y. Yu and S. T. Acton, “Speckle reducing anisotropic diffusion,” IEEE Transactions on Image Processing, vol. 11, no. 11, pp. 1260–1270, 2002. View at Publisher · View at Google Scholar · View at Scopus
  8. C. P. Loizou, V. Murray, M. S. Pattichis, M. Pantziaris, and C. S. Pattichis, “Multiscale amplitude-modulation frequency-modulation (AM-FM) texture analysis of ultrasound images of the intima and media layers of the carotid artery,” IEEE Transactions on Information Technology in Biomedicine, vol. 15, no. 2, pp. 178–188, 2011. View at Publisher · View at Google Scholar · View at Scopus
  9. M. S. Pattichis, “Multidimensional AM-FM models and methods for biomedical image computing,” in Proceedings of the 34th IEEE Annual International Conference of the Engineering in Medicine and Biology Society, pp. 5641–5644, September 2009.
  10. M. S. Pattichis and A. C. Bovik, “Analyzing image structure by multidimensional frequency modulation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 5, pp. 753–766, 2007. View at Publisher · View at Google Scholar · View at Scopus
  11. V. Murray, P. Rodríguez, and M. S. Pattichis, “Multiscale AM-FM demodulation and image reconstruction methods with improved accuracy,” IEEE Transactions on Image Processing, vol. 19, no. 5, pp. 1138–1152, 2010. View at Publisher · View at Google Scholar · View at Scopus
  12. J. P. Havlicek, D. S. Harding, and A. C. Bovik, “The multicomponent AM-FM image representation,” IEEE Transactions on Image Processing, vol. 5, no. 6, pp. 1094–1100, 1996. View at Publisher · View at Google Scholar · View at Scopus
  13. J. P. Havlicek, D. S. Harding, and A. C. Bovik, “Multidimensional quasi-eigenfunction approximations and multicomponent AM-FM models,” IEEE Transactions on Image Processing, vol. 9, no. 2, pp. 227–242, 2000. View at Publisher · View at Google Scholar · View at Scopus
  14. M. S. Pattichis, C. S. Pattichis, M. Avraam, A. Bovik, and K. Kyriacou, “AM-FM texture segmentation in electron microscopic muscle imaging,” IEEE Transactions on Medical Imaging, vol. 19, no. 12, pp. 1253–1258, 2000. View at Google Scholar · View at Scopus
  15. S. Lee, M. S. Pattichis, and A. C. Bovik, “Foveated video quality assessment,” IEEE Transactions on Multimedia, vol. 4, no. 1, pp. 129–132, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. S. Lee, M. S. Pattichis, and A. C. Bovik, “Foveated video compression with optimal rate control,” IEEE Transactions on Image Processing, vol. 10, no. 7, pp. 977–992, 2001. View at Publisher · View at Google Scholar · View at Scopus
  17. C. Agurto, V. Murray, E. Barriga et al., “Multiscale AM-FM methods for diabetic retinopathy lesion detection,” IEEE Transactions on Medical Imaging, vol. 29, no. 2, pp. 502–512, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. N. E. Huang, Z. Shen, S. R. Long et al., “The empirical mode decomposition and the Hubert spectrum for nonlinear and non-stationary time series analysis,” Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 454, no. 1971, pp. 903–995, 1998. View at Google Scholar · View at Scopus
  19. P. Flandrin, G. Rilling, and P. Gonçalvés, “Empirical mode decomposition as a filter bank,” IEEE Signal Processing Letters, vol. 11, no. 2, pp. 112–114, 2004. View at Publisher · View at Google Scholar · View at Scopus
  20. G. Rilling, P. Flandrin, and P. Goncalves, “On empirical mode decomposition and its algorithms,” in Proceedings of the IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03), vol. 3, pp. 8–11, 2003.
  21. C. P. Loizou, C. S. Pattichis, C. I. Christodoulou, R. S. H. Istepanian, M. Pantziaris, and A. Nicolaides, “Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 52, no. 10, pp. 1653–1669, 2005. View at Publisher · View at Google Scholar · View at Scopus
  22. C. P. Loizou CS Pattichis, Despeckle Filtering Algorithms and Software for Ultrasound Imaging, Synthesis Lectures on Algorithms and Software for Engineering, Morgan & Claypool, San Rafael, Calif, USA, 2008.
  23. A Philips Medical System Company, “Comparison of image clarity, SonoCT real-time compound imaging versus conventional 2D ultrasound imaging,” Tech. Rep., ATL Ultrasound, 2001. View at Google Scholar
  24. A. Nicolaides, M. Sabetai, S. K. Kakkos et al., “The Asymptomatic Carotid Stenosis and Risk of Stroke (ACSRS) study. Aims and result of quality control,” International Angiology, vol. 22, no. 3, pp. 263–272, 2003. View at Google Scholar · View at Scopus
  25. T. Elatrozy, A. Nicolaides, T. Tegos, A. Z. Zarka, M. Griffin, and M. Sabetai, “The effect of B-mode ultrasonic image standardisation on the echodensity of symptomatic and asymptomatic carotid bifurcation plaques,” International Angiology, vol. 17, no. 3, pp. 179–186, 1998. View at Google Scholar · View at Scopus
  26. C. P. Loizou, C. S. Pattichis, M. Pantziaris, T. Tyllis, and A. Nicolaides, “Quality evaluation of ultrasound imaging in the carotid artery based on normalization and speckle reduction filtering,” Medical and Biological Engineering and Computing, vol. 44, no. 5, pp. 414–426, 2006. View at Publisher · View at Google Scholar · View at Scopus
  27. J. S. Lee, “Digital image enhancement and noise filtering by using local statistics,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 2, no. 2, pp. 165–168, 1980. View at Google Scholar · View at Scopus
  28. V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A model for radar images and its application for adaptive digital filtering of multiplicative noise,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 2, pp. 157–166, 1982. View at Google Scholar · View at Scopus
  29. M. Kuwahara, K. Hachimura, S. Eiho, and M. Kinoshita, Digital Processing of Biomedical Images, Edited by K. Preston and M. Onoe, Plenum Publishing Corporation, 1976.
  30. A. Nieminen, P. Heinonen, and Y. Neuvo, “A new class of detail-preserving filters for image processing,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 9, no. 1, pp. 74–90, 1987. View at Google Scholar · View at Scopus
  31. K. Z. Abd-Elmoniem, A.-B. M. Youssef, and Y. M. Kadah, “Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion,” IEEE Transactions on Biomedical Engineering, vol. 49, no. 9, pp. 997–1014, 2002. View at Publisher · View at Google Scholar · View at Scopus
  32. D. J. Williams and M. Shah, “A Fast algorithm for active contours and curvature estimation,” CVGIP: Image Understanding, vol. 55, no. 1, pp. 14–26, 1992. View at Google Scholar · View at Scopus
  33. C. P. Loizou, C. S. Pattichis, M. Pantziaris, T. Tyllis, and A. Nicolaides, “Snakes based segmentation of the common carotid artery intima media,” Medical and Biological Engineering and Computing, vol. 45, no. 1, pp. 35–49, 2007. View at Publisher · View at Google Scholar · View at Scopus
  34. W. J. Conover, Practical Nonparametric Statistics, John Wiley & Sons, New York, NY, USA, 3rd edition, 1999.
  35. A. Mittal, R. Soundararajan, and A. C. Bovik, “Making a completely blind image quality analyser,” IEEE Signal Processing Letters, vol. 22, no. 3, pp. 209–212, 2013. View at Google Scholar
  36. A. Schmidt-Trucksäss, D. Grathwohl, A. Schmid et al., “Structural, functional, and hemodynamic changes of the common carotid artery with age in male subjects,” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 19, no. 4, pp. 1091–1097, 1999. View at Google Scholar · View at Scopus
  37. A. N. Nicolaides, S. K. Kakkos, M. Griffin et al., “Effect of image normalization on carotid plaque classification and the risk of ipsilateral hemispheric ischemic events: results from the Asymptomatic Carotid Stenosis and Risk of Stroke study,” Vascular, vol. 13, no. 4, pp. 211–221, 2005. View at Publisher · View at Google Scholar · View at Scopus
  38. A. Mojsilović, M. Popović, N. Amodaj, R. Basić, and M. Ostojić, “Automatic segmentation of intravascular ultrasound images: a texture-based approach,” Annals of Biomedical Engineering, vol. 25, no. 6, pp. 1059–1071, 1997. View at Google Scholar · View at Scopus
  39. A. C. Bovik, “On detecting edges in speckle imagery,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 36, no. 10, pp. 1618–1627, 1988. View at Publisher · View at Google Scholar · View at Scopus
  40. C. P. Loizou, S. Petroudi, C. S. Pattichis, M. Pantziaris, and A. N. Nicolaides, “An integrated system for the segmentation of atherosclerotic carotid plaque in ultrasound video,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 61, no. 1, pp. 86–101, 2014. View at Google Scholar
  41. C. P. Loizou, C. Theofanous, M. Pantziaris et al., “Despeckle filtering toolbox for medical ultrasound video,” International Journal of Monitoring and Surveillance Technologies Research, vol. 4, no. 1, pp. 61–79, 2013. View at Google Scholar