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Cardiac Motion Estimation Using a ProActive Deformable Model: Evaluation and Sensitivity Analysis

  • Conference paper
Statistical Atlases and Computational Models of the Heart (STACOM 2010)

Abstract

To regularize cardiac motion recovery from medical images, electromechanical models are increasingly popular for providing a priori physiological motion information. Although these models are macroscopic, there are still many parameters to be specified for accurate and robust recovery. In this paper, we provide a sensitivity analysis of a pro-active electromechanical model-based cardiac motion tracking framework by studying the impacts of its model parameters. Our sensitivity analysis differs from other works by evaluating the motion recovery through a synthetic image sequence with known displacement field as well as cine and tagged MRI sequences. This analysis helps to identify which parameters should be estimated from patient-specific data and which ones can have their values set from the literature.

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References

  1. Sermesant, M., Delingette, H., Ayache, N.: An electromechanical model of the heart for image analysis and simulation. IEEE Transactions on Medical Imaging 25(5), 612–625 (2006)

    Article  Google Scholar 

  2. Wong, K.C.L., Zhang, H., Liu, H., Shi, P.: Physiome-model-based state-space framework for cardiac deformation recovery. Academic Radiology 14(11), 1341–1349 (2007)

    Article  Google Scholar 

  3. Sundar, H., Davatzikos, C., Biros, G.: Biomechanically-constrained 4D estimation of myocardial motion. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009. LNCS, vol. 5762, pp. 257–265. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  4. Nash, M.: Mechanics and Material Properties of the Heart using an Anatomically Accurate Mathematical Model. PhD thesis, The University of Auckland (1998)

    Google Scholar 

  5. Niederer, S., Rhode, K., Razavi, R., Smith, N.: The importance of model parameters and boundary conditions in whole organ models of cardiac contraction. In: Ayache, N., Delingette, H., Sermesant, M. (eds.) FIMH 2009. LNCS, vol. 5528, pp. 348–356. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Sermesant, M., Konukog̃lu, E., Delingette, H., Coudière, Y., Chinchapatnam, P., Rhode, K.S., Razavi, R., Ayache, N.: An anisotropic multi-front fast marching method for real-time simulation of cardiac electrophysiology. In: Sachse, F.B., Seemann, G. (eds.) FIHM 2007. LNCS, vol. 4466, pp. 160–169. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  7. Ourselin, S., Roche, A., Prima, S., Ayache, N.: Block matching: a general framework to improve robustness of rigid registration of medical images. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 557–566. Springer, Heidelberg (2000)

    Google Scholar 

  8. Sainte-Marie, J., Chapelle, D., Cimrman, R., Sorine, M.: Modeling and estimation of the cardiac electromechanical activity. Computers and Structures 84, 1743–1759 (2006)

    Article  MathSciNet  Google Scholar 

  9. Toussaint, N., Mansi, T., Delingette, H., Ayache, N., Sermesant, M.: An integrated platform for dynamic cardiac simulation and image processing: application to personalised tetralogy of fallot simulation. In: Eurographics Workshop on Visual Computing for Biomedicine (VCBM) (2008)

    Google Scholar 

  10. Cerqueira, M.D., Weissman, N.J., Dilsizian, V., Jacobs, A.K., Kaul, S., Laskey, W.K., Pennell, D.J., Rumberger, J.A., Ryan, T., Verani, M.S.: Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart: a statement for healthcare professionals from the cardiac imaging committee of the council on clinical cardiology of the American Heart Association. Circulation 105, 539–542 (2002)

    Article  Google Scholar 

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© 2010 Springer-Verlag Berlin Heidelberg

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Wong, K.C.L. et al. (2010). Cardiac Motion Estimation Using a ProActive Deformable Model: Evaluation and Sensitivity Analysis. In: Camara, O., Pop, M., Rhode, K., Sermesant, M., Smith, N., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. STACOM 2010. Lecture Notes in Computer Science, vol 6364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15835-3_16

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  • DOI: https://doi.org/10.1007/978-3-642-15835-3_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15834-6

  • Online ISBN: 978-3-642-15835-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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