A new approach to analysis of RF ultrasound echo signals for tissue characterization: Animal studies

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 6513, Issue , 2007, Pages

  Moradi, Mehdi ^a   Mousavi, Parvin ^a   Isotalo, Phillip A ^a   Siemens, David R ^a   Sauerbrei, Eric E ^a   Abolmaesumi, Purang ^a  

^a QUEEN S UNIVERSITY   (Canada)

Author keywords

Fractal dimension; Time series analysis; Tissue characterization; Ultrasound RF echo signals

Indexed keywords

TISSUE CHARACTERIZATION; ULTRASOUND RF ECHO SIGNALS;

BACKSCATTERING; FRACTAL DIMENSION; IMAGE ANALYSIS; SIGNAL ANALYSIS; TIME SERIES ANALYSIS; TISSUE;

ULTRASONICS;

EID: 35148835279     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.708630     Document Type: Conference Paper

References (24)

1. M. Moradi, P. Abolmaesumi, P. Isotalo, D. Siemens, E. Sauerbrei, and P. Mousavi, "Detection of prostate cancer from RF ultrasound echo signals using fractal analysis," in Proceedings of IEEE EMBC2006, pp. 2400-2403, 2006.
2. M. Moradi, P. Abolmaesumi, P. A. Isotalo, D. R. Siemens, E. E. Sauerbrei, and P. Mousavi, "A new feature for detection of prostate cancer based on RF ultrasound echo signals," in Proceedings of the 2006 IEEE International Ultrasonics Symposium, (Vancouvre, BC), October 2006. To appear.
3. F. L. Lizzi, E. J. Feleppa, M. Astor, and A. Kalisz, "Statistics of ultrasonic spectral parameters for prostate and liver examination," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 44(4), pp. 935-942, 1997.
4. J. C. Bamber and C. R. Hill, "Acoustic properties of normal and cancerous human liver, dependence on pathological condition," Ultrasound in Medicine and Biology 7, pp. 121-133, 1981.
5. F. T. D'Astous and F. S. Foster, "Frequency dependence of ultrasound attenuation and backscatter in breast tissue," Ultrasound in Medicine and Biology 12(10), pp. 795-808, 1986.
6. U. Scheipers, H. Ermert, H. J. S. M. Garcia-Schurmann, T. Senge, and S. Philippou, "Ultrasonic multifeature tissue characterization for prostate diagnosis," Ultrasound Med. Biol. 20(8), pp. 1137-1149, 2003.
7. E. J. Feleppa, A. Kalisz, J. B. Sokil-Melgar, F. L. Lizzi, T. Liu, A. L. Rosado, M. C. Shao, W. R. Fair, Y. Wang, M. S. Cookson, V. E. Reuter, and W. D. W. Heston, "Typing of prostate tissue by ultrasonic spectrum analysis," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 43(4), pp. 609-619, 1996.
8. G. Schmitz and H. Ermert, "Tissue-characterization of the prostate using radio frequency ultrasonic signals," IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 46(1), pp. 126-138, 1999.
9. A. J. Jensen, Imaging of Complex Media with Acoustic and Siesmic Waves, vol. 84 of Topics in Applied Physics, ch. Ultrasound and its modeling, pp. 135-164. Springer-Verlag, 2002.
10. M. Linzer and S. J. Norton, "Ultrasonic tissue characterization, " Annual reviews of Biophysics and Bioengineering 11, pp. 303-329, 1982.
11. F. L. Lizzi, M. Greenebaum, E. J. Feleppa. M. Elbaum, and D. J. Coleman, "Theoretical framework for spectrum analysis in ultrasonic tissue characterization," Journal of the Acoustic Society of America 73(3), pp. 1366-1373, 1983.
12. E. J. Feleppa, F. L. Lizzi, D. J. Coleman, and M. M. Yaremko, "Diagnostic spectrum analysis in ophthalmology: a physical perspective," Ultrasound in Medicine and Bilogy 12(8), pp. 623-631, 1986.
13. F. L. Lizzi, E. J. Feleppa, S. K. Alam, and X. C. Deng, "Ultrasonic spectrum analysis for tissue evaluation," Pattern Recognition Letters 24, pp. 637-658, 2003.
14. H. Shono, C. K. P. A. L. Goldberger, M. Shono, and H. Sugimori, "A new method to determine a fractal dimension of non-stationary biological time-serial data," Computers in Biology and Medicine 30(4), pp. 237-245, 2000.
15. B. B. Mandelbrot, Gaussian Self-Affinity and Fractals, Springer, Harrisonburg, VA, 2002.
16. A. Accardo, M. Affinito, M. Carrozzi, and F. Bouquet, "Use of the fractal dimension for the analysis of electroencephalographic time series," Biological Cybernetics 77(5), pp. 339-350, 1997.
17. G. Henderson, E. Ifeachor, N. Hudson, C. Goh, N. Outram, Wimalaratna, C. D. Percio, and F. Vecchio, "Development and assessment of methods for detecting dementia using the human electroencephalogram," IEEE Transactions on Biomedical Engineering 53(8), pp. 1557-1668, 2006.
18. D. J. Marsh, J. L. Osborn, and A. J. Cowley, "1/f fluctuations in arterial pressure and regulation of renal blood flow in dogs," The American Journal of Physiology 258, pp. F1394-400, 1990.
19. F. Beckers, B. Verheyden, K. Couckuyt, and A. Aubert, "Fractal dimension in health and heart failure," Biomedizinische Technik. Biomedical Engineering 51(4), pp. 194-197, 2006.
20. M. Katz, "Fractals and the analysis of waveforms," Comp. Biol. Med. 18(3), pp. 145-156, 1988.
21. T. Higuchi, "Approach to an irregular time series on the basis of the fractal theory," Physica D 31(2), pp. 277-283, 1988.
22. A. Petrosian, "Kolmogorov complexity of finite sequences and recognition of different preictal EEG patterns," in Proceedings of the Eighth IEEE Symposium on Computer-Based Medical Systems, pp. 212-217. 1995.
23. R. Esteller, G. Vachtsevanos, J. Echauz, and B. Litt, "A comparison of fractal dimension algorithms," IEEE Transactions on Circuits and Systems 48(2), pp. 177-183, 2001.
24. R. V. Hogg and J. Ledolter, Engineering Statistics, MacMillan, 1987.