Gamma mixture classifier for plaque detection in intravascular ultrasonic images

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

Volumn 61, Issue 1, 2014, Pages 44-61

  Vegas Sánchez Ferrero, Gonzalo ^a   Seabra, José ^b   Rodriguez Leor, Oriol ^c   Serrano Vida, Angel ^d   Aja Fernáaez, Santiago ^a   Palencia, César ^a   Martín Fernández, Marcos ^a   Sanches, Joao ^b  

^a UNIVERSITY OF VALLADOLID   (Spain)

^b INSTITUTE FOR SYSTEMS AND ROBOTICS   (Portugal)

^c HOSPITAL UNIVERSITARI GERMANS TRIAS I PUJOL   (Spain)

^d HOSPITAL GENERAL DE GRANOLLERS   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

CHARACTERIZATION; DIAGNOSIS; HISTOLOGY; SPECKLE; TISSUE; ULTRASONIC IMAGING; ULTRASONICS;

AUTOMATIC FILTERING; CLASSIFICATION RESULTS; NAKAGAMI DISTRIBUTION; PLAQUE CHARACTERIZATIONS; RAYLEIGH DISTRIBUTIONS; TISSUE COMPOSITION; TWO-PARAMETER MODELS; VULNERABLE PLAQUES;

MIXTURES;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; CORONARY ARTERY DISEASE; CORONARY BLOOD VESSEL; ECHOGRAPHY; ENDOSCOPIC ECHOGRAPHY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CORONARY ARTERY DISEASE; CORONARY VESSELS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; ULTRASONOGRAPHY, INTERVENTIONAL;

EID: 84892405548     PISSN: 08853010     EISSN: None     Source Type: Journal    
DOI: 10.1109/TUFFC.2014.6689775     Document Type: Article

References (54)

1. L . G. Spagnoli, A. Mauriello, G. Sangiorgi, S. Fratoni, E. Bonanno, R. S. Schwartz, D. G. Piepgras, R. Pistolese, A. Ippoliti, and D. R. Holmes Jr., "Extracranial thrombotically active carotid plaque as a risk factor for ischemic stroke," JAMA, vol. 292, no. 15, pp. 1845-1852, 2004. (Pubitemid 40169295)
2. E. Escolar, G. Weigold, A. Fuisz, and J. N. Weissman, "New imaging techniques for diagnosing coronary artery disease," CMAJ, vol. 174, no. 4, pp. 487-495, 2006.
3. J. E. Wilhjelm, M.-L. M. Gronholdt, B. Wiebe, S. K. Jespersen, L. K. Hansen, and H. Sillesen, "Quantitative analysis of ultrasound Bmode images of carotid atherosclerotic plaque: Correlation with visual classification and histological examination," IEEE Trans. Med. Imaging, vol. 17, no. 6, pp. 910-922, 1998. (Pubitemid 128747749)
4. N . M. El-Barghouty, G. Geroulakos, A. Nicolaides, A. Androulakis, and V. Bahal, "Computer-assisted carotid plaque characterisation," Eur. J. Vasc. Endovasc. Surg., vol. 9, no. 4, pp. 389-393, 1995.
5. N . M. El-Barghouty, T. Levine, S. Ladva, A. Flanagan, and A. Nicolaides, "Histological verification of computerised carotid plaque characterisation," Eur. J. Vasc. Endovasc. Surg., vol. 11, no. 4, pp. 414-416, 1996. (Pubitemid 26192845)
6. M. I. Matsagas, S. N. Vasdekis, A. G. Gugulakis, A. Lazaris, M. Foteinou, and M. N. Sechas, "Computer-assisted ultrasonographic analysis of carotid plaques in relation to cerebrovascular symptoms, cerebral infarction, and histology," Ann. Vasc. Surg., vol. 14, no. 2, pp. 130-137, 2000. (Pubitemid 30149065)
7. D . Gonzalo Vegas-Sanchez-Ferrero, M. Martin-Martnez, S. Aja- Fernandez, and C. Palencia, "On the influence of interpolation on probabilistic models for ultrasonic images," in IEEE Int. Symp. Biomedical Imaging, 2010, pp. 292-295.
8. J. Seabra, J. Sanches, F. Ciompi, and P. Radeva, "Ultrasonographic plaque characterization using a Rayleigh mixture model," in IEEE Int. Symp. Biomedical Imaging, 2010, pp. 1-4.
9. J. W. Goodman, "Some fundamental properties of laser speckle," in Laser Speckle and Related Phenomena (Topics in Applied Physics, vol. 9-75). Berlin, Germany: Springer, 1975, pp. 1145-1150.
10. K. Copsey and A. Webb, "Bayesian gamma mixture model approach to radar target recognition," IEEE Trans. Aerosp. Electron. Syst., vol. 39, no. 4, pp. 1201-1217, 2003.
11. M. J. Thijssen, "Ultrasonic speckle formation, analysis and processing applied to tissue characterization," Pattern Recognit. Lett., vol. 24, no. 4-5, pp. 659-675, 2003.
12. P. M. Shankar, J. M. Reid, H. Ortega, C. W. Piccoli, and B. B. Goldberg, "Use of non-Rayleigh statistics for the identification of tumors in ultrasonic B-scans of the breast," IEEE Trans. Med. Imaging, vol. 12, no. 4, pp. 687-692, 1993. (Pubitemid 2022622)
13. P. Mohana Shankar, "A general statistical model for ultrasonic backscattering from tissues," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 47, no. 3, pp. 727-736, 2000.
14. F. Destrempes and G. Cloutier, "A critical review and uniformized representation of statistical distributions modeling the ultrasound echo envelope," Ultrasound Med. Biol., vol. 36, no. 7, pp. 1037-1051, 2010.
15. R . F. Wagner, M. F. Insana, and D. G. Brown, "Statistical properties of radio-frequency and envelope-detected signals with applications to medical ultrasound," J. Opt. Soc. Am. A, vol. 4, no. 5, pp. 910-922, 1987.
16. L . Rayleigh, "On the resultant of a large number of vibrations of the same pitch and of arbitrary phase," Philos. Mag., vol. 10, pp. 73-78, 1880.
17. R . F. Wagner, S. W. Smith, J. M. Sandrik, and H. Lopez, "Statistics of speckle in ultrasound B-scans," IEEE Trans. Sonics Ultrason., vol. 30, no. 3, pp. 156-163, 1983.
18. C . B. Burckhardt, "Speckle in ultrasound B-mode scans," IEEE Trans. Sonics Ultrason., vol. 25, no. 1, pp. 1-6, 1978. (Pubitemid 8381750)
19. S . O. Rice, "Mathematical analysis of random noise," Bell Syst. Tech. J., vol. 23, no. 3, pp. 282-332, 1944.
20. M. Nakagami, "Study of the resultant amplitude of many vibrations whose phases and amplitudes are at random," J. Inst. Electron. Commun. Eng. Jpn., vol. 24, no. 202, pp. 17-26, 1940.
21. T. A. Tuthill, R. H. Sperry, and K. J. Parker, "Deviations from Rayleigh statistics in ultrasonic speckle," Ultrason. Imaging, vol. 10, no. 2, pp. 81-89, 1988.
22. E. Jakeman, "Speckle statistics with a small number of scatterers," Opt. Eng., vol. 23, no. 4, pp. 453-461, 1984. (Pubitemid 14626353)
23. E. Jakeman, "On the statistics of K-distributed noise," J. Phys. Math. Gen., vol. 13, no. 1, pp. 31-48, 1980.
24. V. Dutt and J. F. Greenleaf, "Ultrasound echo envelope analysis using a homodyned k distribution signal model," Ultrason. Imaging, vol. 16, no. 4, pp. 265-287, 1994.
25. E. Jakeman and R. J. A. Tough, "Generalized K distribution: A statistical model for weak scattering," J. Opt. Soc. Am. A, vol. 4, no. 9, pp. 1764-1772, 1987.
26. T. Eltoft, "Modeling the amplitude statistics of ultrasonic images," IEEE Trans. Med. Imaging, vol. 25, no. 2, pp. 229-240, 2006. (Pubitemid 43172577)
27. M. Nakagami, "The m-distribution - A general formula of intensity distribution of rapid fading," in Statistical Methods in Radio Wave Propagation, Proceedings of a Symposium Held June 18-20, 1958, W. C. Hoffmann, Ed., Elmsford, NY: Pergamon Press, 1960, pp. 3-36.
28. F. Destrempes, J. Meunier, M. F. Giroux, G. Soulez, and G. Cloutier, "Segmentation of plaques in sequences of ultrasonic B-mode images of carotid arteries based on motion estimation and a Bayesian model," IEEE Trans. Biomed. Eng., vol. 58, no. 8, pp. 2202-2211, 2011.
29. R . K. Saha and M. C. Kolios, "Effects of cell spatial organization and size distribution on ultrasound backscattering," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 58, no. 10, pp. 2118-2131, 2011.
30. J. C. Seabra, F. Ciompi, O. Pujol, J. Mauri, P. Radeva, and J. Sanches, "Rayleigh mixture model for plaque characterization in intravascular ultrasound," IEEE Trans. Biomed. Eng., vol. 58, no. 5, pp. 1314-1324, 2011.
31. A . P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. R. Stat. Soc., B, vol. 39, no. 1, pp. 1-38, 1977.
32. T. K. Moon, "The expectation-maximization algorithm," IEEE Signal Process. Mag., vol. 13, no. 6, pp. 47-60, 1996. (Pubitemid 126518983)
33. Z. Tao, H. D. Tagare, and J. D. Beaty, "Evaluation of four probability distribution models for speckle in clinical cardiac ultrasound images," IEEE Trans. Med. Imaging, vol. 25, no. 11, pp. 1483-1491, 2006. (Pubitemid 44711696)
34. M. M. Nillesen, R. G. Lopata, I. H. Gerrits, L. Kapusta, J. M. Thijssen, and C. L. de Korte, "Modeling envelope statistics of blood and myocardium for segmentation of echocardiographic images," Ultrasound Med. Biol., vol. 34, no. 4, pp. 674-680, 2008. (Pubitemid 351417691)
35. P. M. Shankar, F. Forsberg, and L. Lown, "Statistical modeling of atherosclerotic plaque in carotid B mode images - A feasibility study," Ultrasound Med. Biol., vol. 29, no. 9, pp. 1305-1309, 2003. (Pubitemid 37211331)
36. S . Atapattu, C. Tellambura, and H. Jiang, "A mixture gamma distribution to model the SNR of wireless channels," IEEE Trans. Wirel. Comm., vol. 10, no. 12, pp. 4193-4203, 2011.
37. A . Taki, H. Hetterich, A. Roodaki, S. K. Setarehdan, G. Unal, J. Rieber, N. Navab, and A. Konig, "A new approach for improving coronary plaque component analysis based on intravascular ultrasound images," Ultrasound Med. Biol., vol. 36, no. 8, pp. 1245-1258, 2010.
38. F. Ciompi, O. Pujol, C. Gatta, O. Rodriguez-Leor, J. Mauri-Ferre, and P. Radeva, "Fusing in-vitro and in-vivo intravascular ultrasound data for plaque characterization," Int. J. Cardiovasc. Imaging, vol. 26, no. 7, pp. 763-779, 2010.
39. A . Nair, B. D. Kuban, E. M. Tuzcu, P. Schoenhagen, S. E. Nissen, and D. G. Vince, "Coronary plaque classification with intravascular ultrasound radiofrequency data analysis," Circulation, vol. 106, no. 17, pp. 2200-2206, 2002. (Pubitemid 35222213)
40. W. C. Roberts and A. A. Jones, "Quantitation of coronary arterial narrowing at necropsy in sudden coronary death: Analysis of 31 patients and comparison with 25 control subjects," Am. J. Cardiol., vol. 44, no. 1, pp. 39-45, 1979. (Pubitemid 9216890)
41. W. Hardle, Smoothing Techniques: With Implementation in S (Springer Series in Statistics). New York, NY: Springer, 1990.
42. F. Destrempes, J. Meunier, M.-F. Giroux, G. Soulez, and G. Cloutier, "Segmentation in ultrasonic B-mode images of healthy carotid arteries using mixtures of Nakagami distributions and stochastic optimization," IEEE Trans. Med. Imaging, vol. 28, no. 2, pp. 215-229, 2009.
43. R . M. Dudley, Uniform Central Limit Theorems, 1st ed., Cambridge, UK: Cambridge University Press, 1999.
44. M. A. T. Figueiredo and A. K. Jain, "Unsupervised learning of finite mixture models," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 3, pp. 381-396, 2002. (Pubitemid 35289353)
45. A . R. Webb, "Gamma mixture models for target recognition," Pattern Recognit., vol. 33, no. 12, pp. 2045-2054, 2000.
46. D . M. Titterington, A. F. Smith, and U. E. Makov, Statistical Analysis of Finite Mixture Distributions. (Wiley Series in Probability and Mathematical Statistics). New York, NY: Wiley, 1992.
47. G. Schwarz, "Estimating the dimension of a model," Ann. Stat., vol. 6, no. 2, pp. 461-464, 1978.
48. T. G. Dietterich and G. Bakiri, "Solving multiclass learning problems via error-correcting output codes," J. Artif. Intell. Res., vol. 2, pp. 263-286, 1995.
49. R . E. Schapire, "Using output codes to boost multiclass learning problems," in Proc. 14th Int. Conf. Machine Learning, 1997, pp. 313-321.
50. J. Demšar, "Statistical comparisons of classifiers over multiple data sets," J. Mach. Learn. Res., vol. 7, pp. 1-30, Dec. 2006. (Pubitemid 43022939)
51. G. Vegas-Sanchez-Ferrero, S. Aja-Fernandez, M. Martin-Fernandez, A. F. Frangi, and C. Palencia, "Probabilistic-driven oriented speckle reducing anisotropic diffusion with application to cardiac ultrasonic images," in Proc. 13th Int. Conf. Medical Image Computing and Computer-Assisted Intervention: Part I, 2010, pp. 518-525.
52. M. Merkle, "Logarithmic convexity and inequalities for the gamma function," J. Math. Anal. Appl., vol. 203, no. 2, pp. 369-380, 1996. (Pubitemid 126175343)
53. I. Franjic, S. Khalid, and J. Pecaric, "On the refinements of the Jensen-Steffensen inequality," J. Inequal. Appl., vol. 2011, art. no. 12, Jun. 2011.
54. H. Alzer, "On some inequalities for the gamma and psi functions," Math. Comput., vol. 66, no. 217, pp. 373-389, 1997. (Pubitemid 127423923)