Suppression of IVUS Image Rotation. A Kinematic Approach

  • Misael Rosales
  • Petia Radeva
  • Oriol Rodriguez
  • Debora Gil
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3504)


IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.


Intravascular Ultrasound Rotation Center IVUS Image Kinematic Approach Minimal Total Energy 
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  1. 1.
    Yock, P., Linker, D., et al.: Intravascular two dimensional catheter ultrasound, Initial clinical studies. Circulations (78), II–21 (1988)Google Scholar
  2. 2.
    Graham, S., Brands, D., et al.: Assesment of arterial wall morphology using intravascular ultrasound in vitro and in patient. Circulations, II–56 (1989)Google Scholar
  3. 3.
    Metz, J., Paul, G., et al.: Intravascular Ultrasound Imaging. In: Tobis, J.M., Yock, P.G. (eds.). Churchil Livinstone Inc. (1992)Google Scholar
  4. 4.
    Metz Jonas, A., Paul, G., et al.: Intravascular ultrasound basic interpretation, in Beyond Angiography. Intravascular Ultrasound, State of the art, Congress of the ESC Viena-Austria, California, USA, vol. XX (1998)Google Scholar
  5. 5.
    Jumbo, G., Raimund, E.: Novel techniques of coronary artery imaging, in Beyond Angiography. Intra Vascular Ultrasound, state of the art, Congress of the ESC Viena-Austria, University of Essen, Germany, vol.  XX (1998)Google Scholar
  6. 6.
    Di Mario, C., et al.: The angle of incidence of the ultrasonic beam a critical factor for the image quality in intravascular ultrasonography. Am. Heart J. 125, 442–448 (1993)CrossRefGoogle Scholar
  7. 7.
    Arendt Jesen, J.: Linear Descripcion of Ultrasound Imaging System. Notes for the international Summer School on Advanced Ultrasound Imaging, Technical University of Denamark (2001)Google Scholar
  8. 8.
    Berry, E., et al.: Intravascular ultrasound-guided interventions in coronary artery disease. NHS R D HTA Programme (2000)Google Scholar
  9. 9.
    Patrick, H.W.: Inteligencia Artificial. Addison Wesley Iberoamericana, Reading (1994)Google Scholar
  10. 10.
    Korte Chris, L.: Intravascular Ultrasound Elastography. Interuniversity Cardiology Institute of the Netherlands, ICIN (1999)Google Scholar
  11. 11.
    Mazumdar, J.: Biofluids Mechanics. World Scientific Publishing, Singapore (1992)Google Scholar
  12. 12.
    Young, B., Heath, J.: Wheater’s, Histología Funcional, 4ta edición, Ediciones Hardcourt, S.A (2000)Google Scholar
  13. 13.
    Boston Scientific Corporation, Scimed division, The ABCs of IVUS (1998)Google Scholar
  14. 14.
    Rosales, M., Radeva, P., et al.: Simulation Model of Intravascular Ultrasound Images. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3217, pp. 200–207. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  15. 15.
    Vogt, M., et al.: Strutural analysis of the skin using high frequency broadband ultrasound in the range from 30 to 140 mhz. In: IEEE Internationalk Ultrasonics Syposium, Sendai, Japan (1998)Google Scholar
  16. 16.
    Andrew, W., et al.: Direct Least Square Fitting of Ellipses. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(5), 476–480 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Misael Rosales
    • 1
    • 2
  • Petia Radeva
    • 2
  • Oriol Rodriguez
    • 3
  • Debora Gil
    • 2
  1. 1.Lab. de Física AplicadaFac. de Cs. Dpto. de Física (ULA)MéridaVenezuela
  2. 2.CVC, Edifici OBellaterraSpain
  3. 3.Universitary Hospital ”Germans Tries i Pujol”BadalonaSpain

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