Phase-Based Registration of Cardiac Tagged MR Images by Incorporating Anatomical Constraints

  • Yitian Zhou
  • Mathieu De Craene
  • Maxime Sermesant
  • Olivier Bernard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10124)

Abstract

This paper presents a novel method that combines respective benefits of the tracking-based methods and the Gabor-based non-tracking approaches for improving the motion/strain quantification from tagged MR images. The “tag number constant” concept used in Gabor-based non-tracking methods is integrated into a recent phase-based registration framework. We evaluated our method on both synthetic and real data: (1) on a synthetic data of a normal heart, we found that the constraint improved both longitudinal and circumferential strains accuracies; (2) on 15 healthy volunteers, the proposed method achieved better tracking accuracy compared to three state-of-the-art methods; (3) on one patient dataset, we show that our method is able to distinguish the infarcted segments from the normal ones.

Keywords

Cardiac tagged MR Strain Tag number constant constraint 

References

  1. 1.
    Zhou, Y., Bernard, O., Saloux, E., Manrique, A., Allain, P., Makram-Ebeid, S., De Craene, M.: 3D harmonic phase tracking with anatomical regularization. Med. Image Anal. 26(1), 70–81 (2015)CrossRefGoogle Scholar
  2. 2.
    Osman, N.F., Kerwin, W.S., McVeigh, E.R., Prince, J.L.: Cardiac motion tracking using cine harmonic phase (HARP) magnetic resonance imaging. Magn. Reson. Med. 42(6), 1048 (1999)CrossRefGoogle Scholar
  3. 3.
    Qian, Z., Liu, Q., Metaxas, D.N., Axel, L.: Identifying regional cardiac abnormalities from myocardial strains using nontracking-based strain estimation and spatio-temporal tensor analysis. IEEE Trans. Med. Imaging 30(12), 2017–2029 (2011)CrossRefGoogle Scholar
  4. 4.
    Bruurmijn, L.C.M., Kause, H.B., Filatova, O.G., Duits, R., Fuster, A., Florack, L.M.J., Assen, H.C.: Myocardial deformation from local frequency estimation in tagging MRI. In: Ourselin, S., Rueckert, D., Smith, N. (eds.) FIMH 2013. LNCS, vol. 7945, pp. 284–291. Springer, Heidelberg (2013). doi:10.1007/978-3-642-38899-6_34 CrossRefGoogle Scholar
  5. 5.
    Kause, H.B., Filatova, O.G., Duits, R., Bruurmijn, L.C.M., Fuster, A., Westenberg, J.J.M., Florack, L.M.J., van Assen, H.C.: Direct myocardial strain assessment from frequency estimation in tagging MRI. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds.) STACOM 2013. LNCS, vol. 8330, pp. 212–219. Springer, Heidelberg (2014). doi:10.1007/978-3-642-54268-8_25 CrossRefGoogle Scholar
  6. 6.
    Zhou, Y., De Craene, M., Bernard, O.: Phase-based registration of cardiac tagged mr images using anatomical deformation model. In: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), pp. 617–620. IEEE (2016)Google Scholar
  7. 7.
    Makram-Ebeid, S., Somphone, O.: Non-rigid image registration using a hierarchical partition of unity finite element method. In: 2007 IEEE 11th International Conference on Computer Vision ICCV 2007, pp. 1–8. IEEE (2007)Google Scholar
  8. 8.
    Marchesseau, S., Delingette, H., Sermesant, M., Ayache, N.: Fast parameter calibration of a cardiac electromechanical model from medical images based on the unscented transform. Biomech. Model. Mechanobiol. 12(4), 815–831 (2013)CrossRefGoogle Scholar
  9. 9.
    Tobon-Gomez, C., De Craene, M., Mcleod, K., Tautz, L., Shi, W., Hennemuth, A., Prakosa, A., Wang, H., Carr-White, G., Kapetanakis, S., et al.: Benchmarking framework for myocardial tracking and deformation algorithms: An open access database. Med. Image Anal. 17(6), 632–648 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Yitian Zhou
    • 1
    • 3
  • Mathieu De Craene
    • 1
  • Maxime Sermesant
    • 2
  • Olivier Bernard
    • 3
  1. 1.Philips Research MedisysSuresnesFrance
  2. 2.Inria, Asclepios Research ProjectSophia AntipolisFrance
  3. 3.CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1VilleurbanneFrance

Personalised recommendations