Skip to main content

Atlas-Guided Global Tractography: Imposing a Prior on the Local Track Orientation

  • Conference paper
  • First Online:
Computational Diffusion MRI

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

Since its introduction over a decade ago, diffusion tractography has come a long way from local, deterministic methods, over probabilistic approaches, towards global tractography. Yet, the development of tractography methods has been largely focused on single subject data, and very little on cross-population analysis and inter-subject variability. In this work, we extend global tractography with a prior on the local track orientation distribution (TOD), derived from 20 normal subjects. The proposed method is evaluated in five independent subjects. Results show that adding such prior regularizes the reconstructed track distribution, although registration errors can induce local artefacts. We conclude that atlas-guided global tractography can improve the fibre reconstruction and ultimately detect and quantify inter-subject differences in tractography.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Cabezas, M., Oliver, A., Lladó, X., Freixenet, J., Bach Cuadra, M.: A review of atlas-based segmentation for magnetic resonance brain images. Comput. Meth. Prog. Biomed. 104(3), e158–e177 (2011)

    Article  Google Scholar 

  2. Christiaens, D., Dhollander, T., Maes, F., Sunaert, S., Suetens, P.: Groupwise deformable registration of fiber track sets using track orientation distributions. In: Schultz, T., Nedjati-Gilani, G., Venkataraman, A., O’Donnell, L., Panagiotaki, E. (eds.) Computational Diffusion MRI and Brain Connectivity, Mathematics and Visualization, pp. 151–161. Springer, New York (2014)

    Chapter  Google Scholar 

  3. Cook, P.A., Zhang, H., Awate, S.P., Gee, J.C.: Atlas-guided probabilistic diffusion-tensor fiber tractography. In: 5th International Symposium on Biomedical Imaging: From Nano to Macro—ISBI 2008, pp. 951–954. IEEE (2008)

    Google Scholar 

  4. Descoteaux, M., Deriche, R., Knosche, T., Anwander, A.: Deterministic and probabilistic tractography based on complex fibre orientation distributions. IEEE Trans. Med. Imaging 28(2), 269–286 (2009)

    Article  Google Scholar 

  5. Dhollander, T., Emsell, L., Van Hecke, W., Maes, F., Sunaert, S., Suetens, P.: Track orientation density imaging (TODI) and track orientation distribution (TOD) based tractography. NeuroImage 94, 312–336 (2014)

    Article  Google Scholar 

  6. Fillard, P., Poupon, C., Mangin, J.F.: A novel global tractography algorithm based on an adaptive spin glass model. In: Yang, G.Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) Medical Image Computing and Computer-Assisted Intervention—MICCAI 2009, LNCS, vol. 5761, pp. 927–934. Springer, Berlin (2009)

    Google Scholar 

  7. Fischl, B.: Freesurfer. NeuroImage 62(2), 774–781 (2012)

    Article  Google Scholar 

  8. Glasser, M.F., Sotiropoulos, S.N., Wilson, J.A., Coalson, T.S., Fischl, B., Andersson, J.L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J.R., Van Essen, D.C., Jenkinson, M.: The minimal preprocessing pipelines for the human connectome project. NeuroImage 80, 105–124 (2013)

    Article  Google Scholar 

  9. Hastings, W.K.: Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57(1), 97–109 (1970)

    Article  MathSciNet  MATH  Google Scholar 

  10. Jbabdi, S., Johansen-Berg, H.: Tractography: where do we go from here? Brain Connect. 1(3), 169–183 (2011)

    Article  Google Scholar 

  11. Kreher, B., Mader, I., Kiselev, V.: Gibbs tracking: a novel approach for the reconstruction of neuronal pathways. Magn. Reson. Med. 60(4), 953–963 (2008)

    Article  Google Scholar 

  12. Mangin, J.F., Fillard, P., Cointepas, Y., Le Bihan, D., Frouin, V., Poupon, C.: Toward global tractography. NeuroImage 80, 290–296 (2013)

    Article  Google Scholar 

  13. Mangin, J.F., Poupon, C., Cointepas, Y., Riviere, D., Papadopoulos-Orfanos, D., Clark, C., Régis, J., Le Bihan, D.: A framework based on spin glass models for the inference of anatomical connectivity from diffusion-weighted MR data—a technical review. NMR Biomed. 15(7–8), 481–492 (2002)

    Article  Google Scholar 

  14. Mori, S., van Zijl, P.: Fiber tracking: principles and strategies—a technical review. NMR Biomed. 15(7–8), 468–480 (2002)

    Article  Google Scholar 

  15. O’Donnell, L.J., Golby, A.J., Westin, C.F.: Fiber clustering versus the parcellation-based connectome. NeuroImage 80, 283–289 (2013)

    Article  Google Scholar 

  16. Parker, G.J.: Probabilistic fiber tracking. In: Jones, D.K. (ed.) Diffusion MRI: Theory, Methods, and Applications, pp. 396–408. Oxford University Press, Oxford (2010)

    Chapter  Google Scholar 

  17. Raffelt, D., Tournier, J., Crozier, S., Connelly, A., Salvado, O.: Reorientation of fiber orientation distributions using apodized point spread functions. Magn. Reson. Med. 67(3), 844–855 (2012)

    Article  Google Scholar 

  18. Reisert, M., Mader, I., Anastasopoulos, C., Weigel, M., Schnell, S., Kiselev, V.: Global fiber reconstruction becomes practical. NeuroImage 54(2), 955–962 (2011)

    Article  Google Scholar 

  19. Tournier, J., Calamante, F., Connelly, A.: Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. NeuroImage 35(4), 1459–1472 (2007)

    Article  Google Scholar 

  20. Van Essen, D.C., Smith, S.M., Barch, D.M., Behrens, T.E., Yacoub, E., Ugurbil, K.: The WU-Minn human connectome project: an overview. NeuroImage 80, 62–79 (2013)

    Article  Google Scholar 

  21. Wassermann, D., Makris, N., Rathi, Y., Shenton, M., Kikinis, R., Kubicki, M., Westin, C.F.: On describing human white matter anatomy: The white matter query language. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, Lecture Notes in Computer Science, vol. 8149, pp. 647–654. Springer, Berlin (2013)

    Google Scholar 

  22. Yap, P.T., Gilmore, J.H., Lin, W., Shen, D.: PopTract: population-based tractography. IEEE Trans. Med. Imaging 30(10), 1829–1840 (2011)

    Article  Google Scholar 

  23. Yendiki, A., Panneck, P., Srinivasan, P., Stevens, A., Zöllei, L., Augustinack, J., Wang, R., Salat, D., Ehrlich, S., Behrens, T., Jbabdi, S., Gollub, R., Fischl, B.: Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy. Front. Neuroinformatics 5 (2011)

    Google Scholar 

Download references

Acknowledgements

D. Christiaens is supported by a Ph.D. grant of the Agency for Innovation by Science and Technology (IWT). Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Daan Christiaens .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Christiaens, D., Reisert, M., Dhollander, T., Maes, F., Sunaert, S., Suetens, P. (2014). Atlas-Guided Global Tractography: Imposing a Prior on the Local Track Orientation. In: O'Donnell, L., Nedjati-Gilani, G., Rathi, Y., Reisert, M., Schneider, T. (eds) Computational Diffusion MRI. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-11182-7_11

Download citation

Publish with us

Policies and ethics