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Maximum Likelihood Motion Estimation in 3D Echocardiography through Non-rigid Registration in Spherical Coordinates

  • Conference paper
Functional Imaging and Modeling of the Heart (FIMH 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5528))

Abstract

Automated motion tracking of the myocardium from 3D echocardiography provides insight into heart’s architecture and function. We present a method for 3D cardiac motion tracking using non-rigid image registration. Our contribution is two-fold. We introduce a new similarity measure derived from a maximum likelihood perspective taking into account physical properties of ultrasound image acquisition and formation. Second, we use envelope-detected 3D echo images in the raw spherical coordinates format, which preserves speckle statistics and represents a compromise between signal detail and data complexity. We derive mechanical measures such as strain and twist, and validate using sonomicrometry in open-chest piglets. The results demonstrate the accuracy and feasibility of our method for studying cardiac motion.

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References

  1. Lang, M., Mor-Avi, V., Sugeng, L., Nieman, P., Sahn, D.J.: Three-dimensional echocardiography. Jour. of the Am. Coll. of Cardiology 48(10), 2053–2069 (2006)

    Article  Google Scholar 

  2. Myronenko, A., Song, X., Sahn, D.J.: LV motion tracking from 3D echocardiography using textural and structural information. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 428–435. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  3. Elen, A., Choi, H.F., Loeckx, D., Gao, H., Claus, P., Suetens, P., Maes, F., D’hooge, J.: Three-dimensional cardiac strain estimation using spatio–temporal elastic registration of ultrasound images: A feasibility study. TMI 27(11), 1580–1591 (2008)

    Google Scholar 

  4. Leung, K., van Stralen, M., Nemes, A., Voormolen, M., Voormolen, M., van Burken, G., Geleijnse, M.J.t., Reiber, J., de Jong, N., van der Steen, A., Bosch, J.: Sparse registration for 3D stress echocardiography. Medical Imaging 27(11), 1568–1579 (2008)

    Article  Google Scholar 

  5. Ledesma-Carbayo, M., Kybic, J., Desco, M., Santos, A., Sühling, M., Hunziker, P., Unser, M.: Spatio-temporal nonrigid registration for ultrasound cardiac motion estimation. IEEE Transactions on Medical Imaging 24(9), 1113–1126 (2005)

    Article  Google Scholar 

  6. Sanchez-Ortiz, G., Wright, G., Clarke, N., Declerck, J., Banning, A., Noble, J.: Automated 3-D echocardiography analysis compared with manual delineations and spect muga. IEEE Transactions on Medical Imaging 21(9), 1069–1076 (2002)

    Article  Google Scholar 

  7. Cohen, B., Dinstein, I.: New maximum likelihood motion estimation schemes for noisy ultrasound images. Pattern Recognition 35(2), 455–463 (2002)

    Article  MATH  Google Scholar 

  8. Cobbold, R.S.C.: Foundations of Biomedical Ultrasound. Biomedical Engineering Series. Oxford University Press, Oxford (2006)

    Google Scholar 

  9. Burckhardt, C.B.: Speckle in ultrasound b-mode scans. IEEE Trans. on Sonics and Ultrasonics 25(1) (1978)

    Google Scholar 

  10. Meunier, J.: Tissue motion assessment from 3D echographic speckle tracking. Physics in medicine and biology 43(5), 1241–1254 (1998)

    Article  Google Scholar 

  11. Goodman, J.W.: Speckle Phenomena in Optics. Theory and Applications (2006)

    Google Scholar 

  12. Chandrashekara, R., Mohiaddin, R.H., Rueckert, D.: Daniel rueckert. In: Ayache, N., Delingette, H. (eds.) IS4TM 2003. LNCS, vol. 2673, pp. 88–99. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  13. Roche, A., Malandain, G., Ayache, N.: Unifying maximum likelihood approaches in medical image registration. IJIST 11, 71–80 (2000)

    Google Scholar 

  14. Papoulis, A.: Probability, Random Variables, and Stochastic Processes (1991)

    Google Scholar 

  15. Boukerroui, D., Noble, J.A., Brady, M.: Velocity estimation in ultrasound images: A block matching approach. IPMI 2732, 586–598 (2003)

    Google Scholar 

  16. Revell, J., Mirmehdi, M., McNally, D.: Combined ultrasound speckle pattern similarity measures. In: MIUA, pp. 149–153. BMVA Press (2004)

    Google Scholar 

  17. Song, X., Myronenko, A., Sahn, D.J.: Speckle tracking in 3D echocardiography with motion coherence. In: Comp. Vision and Patt. Recognition (CVPR) (2007)

    Google Scholar 

  18. Linguraru, M.G., Vasilyev, N.V., Marx, G.R., Tworetzky, W., Nido, P.J.D., Howe, R.D.: Fast block flow tracking of atrial septal defects in 4D echo. MIA (2008)

    Google Scholar 

  19. Sloane, N.: Online enc. of integer sequences. A002457, A002802, A020918 (2008)

    Google Scholar 

  20. Miller, K., Bernstein, R., Bluemenson, L.: Generalized rayleigh processes. Quarterly of Applied Mathematics 16, 137–145 (1958)

    Article  MathSciNet  Google Scholar 

  21. Shankar, P.M.: A general statistical model for ultrasonic backscattering from tissues. IEEE T. Ultr., Ferr. and Frequency Control 47(3), 727–736 (2000)

    Article  Google Scholar 

  22. Tan, C.C., Beaulieu, N.C.: Infinite series representations of the bivariate rayleigh and nakagami-m distributions. IEEE Trans. Communications 45(10) (1997)

    Google Scholar 

  23. Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L.G., Leach, M.O., Hawkes, D.J.: Nonrigid registration using free-form deformations: Application to breast MR images. IEEE Trans. Image Processing 18(8), 712–721 (1999)

    Article  Google Scholar 

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Myronenko, A., Song, X., Sahn, D.J. (2009). Maximum Likelihood Motion Estimation in 3D Echocardiography through Non-rigid Registration in Spherical Coordinates. In: Ayache, N., Delingette, H., Sermesant, M. (eds) Functional Imaging and Modeling of the Heart. FIMH 2009. Lecture Notes in Computer Science, vol 5528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01932-6_46

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  • DOI: https://doi.org/10.1007/978-3-642-01932-6_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01931-9

  • Online ISBN: 978-3-642-01932-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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