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Assessing Artery Motion Compensation in IVUS

  • Debora Gil
  • Oriol Rodriguez-Leor
  • Petia Radeva
  • Aura Hernàndez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

Cardiac dynamics suppression is a main issue for visual improvement and computation of tissue mechanical properties in IntraVascular UltraSound (IVUS). Although in recent times several motion compensation techniques have arisen, there is a lack of objective evaluation of motion reduction in in vivo pullbacks. We consider that the assessment protocol deserves special attention for the sake of a clinical applicability as reliable as possible. Our work focuses on defining a quality measure and a validation protocol assessing IVUS motion compensation. On the grounds of continuum mechanics laws we introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; while results in in vivo pullbacks show its reliability in clinical cases.

Keywords

validation standards quality measures IVUS motion compensation conservation laws Fourier development 

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References

  1. 1.
    Wentzel, J., Krams, R., et al.: Relationship between neointimal thickness and shear stress after wallstent implantation in human coronary arteries. Circulation 103(13), 1740–1745 (2001)Google Scholar
  2. 2.
    Garcia, J., Crespo, A., Goicolea, J., Sanmartin, M., Garcia, C.: Study of the evolution of the shear stress on the restenosis after coronary angioplasty. Journal of Biomechanics 39(5), 799–805 (2006)CrossRefGoogle Scholar
  3. 3.
    Kakadiaris, I.A., O’Malley, S.M., Vavuranakis, M., Carlier, S., Metcalfe, R., Hartley, C.J., Falk, E., Naghavi, M.: Signal-processing approaches to risk assessment in coronary artery disease. Technical Report UH-CS-06-09, Department of Computer Science, University of Houston (June 2006)Google Scholar
  4. 4.
    Céspedes, E., Korte, C., van der Steen, A.: Intraluminal ultrasonic palpation: assessment of local cross-sectional tissue stiffness. Ultrasound Med. Biol. 26, 385–396 (2000)CrossRefGoogle Scholar
  5. 5.
    Delachartre, P., Cachard, C., Finet, G., Gerfault, F.L., Vray, D.: Modeling geometric artefacts in intravascular ultrasound imaging. Ultrasound Med. Biol. 25(4), 567–575 (1999)CrossRefGoogle Scholar
  6. 6.
    de Winter, S.A., Hamers, R., Degertekin, M., et al.: Retrospective image-based gating of intracoronary ultrasound images for improved quantitative analysis: The intelligate method. Catheterization and Cardiovascular Interv. 61, 84–94 (1997)CrossRefGoogle Scholar
  7. 7.
    Leung, K.Y.E., Baldewsing, R., Mastik, F., et al.: Motion compensation for intravascular ultrasound palpography for in vivo vulnerable plaque detection. In: IEEE Ultrasonics Symposium, vol. 1, pp. 253–256 (2005)Google Scholar
  8. 8.
    Hernàndez, A., Radeva, P., Tovar, A., Gil, D.: Vessel structures alignment by spectral analysis of ivus sequences. In: Proc. of CVII, MICCAI Workshop (2006)Google Scholar
  9. 9.
    Rosales, M., Radeva, P., Rodriguez, O., Gil, D.: Suppression of IVUS image rotation. In: Frangi, A.F., Radeva, P.I., Santos, A., Hernandez, M. (eds.) FIMH 2005. LNCS, vol. 3504, pp. 359–368. Springer, Heidelberg (2005)Google Scholar
  10. 10.
    Whitaker, S.: Introduction to Fluid Mechanics. Krieger Pub. Co. (1992)Google Scholar
  11. 11.
    Viola, P., Wells, W.M.: Alignment by maximization of mutual information. Journal of Computer Vision 24, 137–154 (1997)CrossRefGoogle Scholar
  12. 12.
    Pratt, W.: Digital Image Processing, 2nd edn. Wiley, New York (1991)zbMATHGoogle Scholar
  13. 13.
    Pluim, J.P.W., Maintz, J.B.A., Viergever, M.A.: Mutual information based registration of medical images: a survey. IEEE Trans. Med. Imag. 22(8), 986–1004 (2003)CrossRefGoogle Scholar
  14. 14.
    Rudin, W.: Complex and Real Analysis. McGraw-Hill, New York (1987)zbMATHGoogle Scholar
  15. 15.
    Rousseeuw, P., Leroy, A.M.: Robust Regression and Outlier Detection. Wiley, West Sussex, England (1987)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Debora Gil
    • 1
  • Oriol Rodriguez-Leor
    • 3
  • Petia Radeva
    • 1
    • 2
  • Aura Hernàndez
    • 1
    • 2
  1. 1.Computer Vision Center, BellaterraSpain
  2. 2.Computer Science Department of UAB, BellaterraSpain
  3. 3.Hospital Universitari Germans Trias i Pujol, BadalonaSpain

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