Generation of Synthetic 4D Cardiac CT Images by Deformation from Cardiac Ultrasound

  • Feng Li
  • James A. White
  • Martin Rajchl
  • Aashish Goela
  • Terry M. Peters
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7815)


In this paper we introduce a method of generating a synthetic 4D cardiac CT dataset using a single (static) CT and 4D ultrasound images. The method performs non-rigid registrations among ultrasound images to obtain deformation fields of patient specific heart motion and applies the deformation fields onto a static CT image to deform it into a series of dynamic CT images. It is the ultimate aim that this novel synthetic CT dataset could be used to generate high spatiotemporal resolution 4D cardiac models for the intra-operative guidance of minimally invasive cardiac intervention. Validations were performed by comparing synthetic CT images to real dynamic CT images.


image guided intervention augmented reality minimally invasive cardiac intervention synthetic CT non-rigid registration 


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  1. 1.
    Dotty, D.B., Flores, J.H., Doty, J.R.: Cardiac valve operations using a partial sternotomy technique. J. Card. Surg. 15, 35–42 (2000)CrossRefGoogle Scholar
  2. 2.
    Vassiliades, T.A., Block, P.C., Cohn, L.H.: The clinical development of percutaneous heart valve technology. J. Thorac. Cardiovasc. Surg. 129, 970–976 (2005)CrossRefGoogle Scholar
  3. 3.
    McVeigh, E.R., Guttman, M.A., Kellman, P., Raval, A.A., Lederman, R.J.: Real-time interactive MRI for cardiovascular interventions. Acad. Radiol. 12, 1221–1227 (2005)CrossRefGoogle Scholar
  4. 4.
    Linte, C.A., Moore, J., Wedlake, C., Bainbridge, D., Guiraudon, G.M., Jones, D.L., Peters, T.M.: Inside the beating heart: An in vivo feasibility study on fusing pre- and intra-operative imaging for minimally invasive therapy. Journal of Computer Assisted Radiology and Surgery 4(2), 113–123 (2009)CrossRefGoogle Scholar
  5. 5.
    Linte, C.A., Moore, J., Wiles, A.D., Wedlake, C., Peters, T.M.: Virtual reality-enhanced ultrasound guidance: A novel technique for intracardiac interventions. Comput. Aided Surg. 13(2), 82–94 (2008)Google Scholar
  6. 6.
    Huang, X., Hill, N.A., Ren, J., Guiraudon, G., Boughner, D., Peters, T.M.: Dynamic 3D ultrasound and MR image registration of the beating heart. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 171–178. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  7. 7.
    Shuman, W.P., Branch, K.R., May, J.M., Mitsumori, L.M., Lockhart, D.W., Dubinsky, T.J., Warren, B.H., Caldwell, J.H.: Prospective versus retrospective ECG gating for 64-detector CT of the coronary arteries: comparison of image quality and patient radiation dose. Radiology 248(2), 431–437 (2008)CrossRefGoogle Scholar
  8. 8.
    Li, F., Lang, P., Rajchl, M., Chen, E.C.S., Guiraudon, G., Peters, T.M.: Towards real-time 3D US-CT registration on the beating heart for guidance of minimally invasive cardiac interventions. In: Proc. SPIE, vol. 8316, p. 831615 (2012)Google Scholar
  9. 9.
    Ledesma-Carbayo, M.J., Kybic, J., Desco, M., Santos, A., Suhling, M., Hunziker, P., Unser, M.: Spatio-temporal nonrigid registration for ultrasound cardiac motion estimation. IEEE Trans. Med. Imaging 24(9), 1113–1126 (2005)CrossRefGoogle Scholar
  10. 10.
    Shi, W., Zhuang, X., Wang, H., Duckett, S., Luong, D.V., Tobon-Gomez, C., Tung, K., Edwards, P.J., Rhode, K.S., Razavi, R.S., Ourselin, S., Rueckert, D.: A Comprehensive Cardiac Motion Estimation Framework Using Both Untagged and 3-D Tagged MR Images Based on Nonrigid Registration. IEEE Trans. Med. Imaging 31(6), 1263–1275 (2012) (Epub February 15, 2012)Google Scholar
  11. 11.
    Wierzbicki, M., Drangova, M., Guiraudon, G.M., Peters, T.M.: Validation of dynamic heart models obtained using non-linear registration for virtual reality training, planning, and guidance of minimally invasive cardiac surgeries. Medical Image Analysis 8(3), 387–401 (2004)CrossRefGoogle Scholar
  12. 12.
    Sundar, H., Litt, H., Shen, D.: Estimating myocardial motion by 4D image warping. Journal Pattern Recognition 42(11), 2514–2526 (2009)CrossRefGoogle Scholar
  13. 13.
    Modat, M., Taylor, Z.A., Barnes, J., Hawkes, D.J., Fox, N.C., Ourselin, S.: Fast free-form deformation using graphics processing units. Comput. Meth. Prog. Bio. 98(3), 278–284 (2010)CrossRefGoogle Scholar
  14. 14.
    Peyrat, J.-M., Delingette, H., Sermesant, M., Pennec, X., Xu, C., Ayache, N.: Registration of 4D time-series of cardiac images with multichannel Diffeomorphic Demons. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part II. LNCS, vol. 5242, pp. 972–979. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Vemuri, B.C., Ye, J., Chen, Y., Leonard, C.M.: Image registration via level-set motion: applications to atlas-based segmentation. Medical Image Analysis 7, 1–20 (2003)CrossRefGoogle Scholar
  16. 16.
    Pluim, J.P.W., Antoine Maintz, J.B., Viergever, M.A.: Mutual information based registration of medical images: a survey. IEEE Trans. Med. Imaging 22(8), 986–1004 (2003)CrossRefGoogle Scholar
  17. 17.
    Rogalla, P., Kloeters, C., Hein, P.A.: CT technology overview: 64-slice and beyond. Radiol. Clin. North Am. 47(1), 1–11 (2009)CrossRefGoogle Scholar
  18. 18.
    Rajchl, M., Yuan, J., Ukwatta, E., Peters, T.M.: Fast interactive multi-region cardiac segmentation with linearly ordered labels. In: 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1409–1412 (2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Feng Li
    • 1
    • 2
  • James A. White
    • 1
    • 3
  • Martin Rajchl
    • 1
    • 2
  • Aashish Goela
    • 4
  • Terry M. Peters
    • 1
    • 2
  1. 1.Imaging Research LaboratoriesRobarts Research InstituteLondonUK
  2. 2.Biomedical Engineering Graduate ProgramWestern UniversityLondonUK
  3. 3.Division of Cardiology, Department of MedicineWestern UniversityLondonUK
  4. 4.Department of Medical ImagingWestern UniversityLondonUK

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