Skip to main content

Advertisement

SpringerLink
Log in
Menu
Find a journal Publish with us
Search
Cart
Book cover

International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2012: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012 pp 57–65Cite as

  1. Home
  2. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012
  3. Conference paper
Joint T1 and Brain Fiber Log-Demons Registration Using Currents to Model Geometry

Joint T1 and Brain Fiber Log-Demons Registration Using Currents to Model Geometry

  • Viviana Siless19,20,
  • Joan Glaunès21,
  • Pamela Guevara22,
  • Jean-François Mangin20,
  • Cyril Poupon20,
  • Denis Le Bihan20,
  • Bertrand Thirion19,20 &
  • …
  • Pierre Fillard19,20 
  • Conference paper
  • 4025 Accesses

  • 11 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7511)

Abstract

We present an extension of the diffeomorphic Geometric Demons algorithm which combines the iconic registration with geometric constraints. Our algorithm works in the log-domain space, so that one can efficiently compute the deformation field of the geometry. We represent the shape of objects of interest in the space of currents which is sensitive to both location and geometric structure of objects. Currents provides a distance between geometric structures that can be defined without specifying explicit point-to-point correspondences. We demonstrate this framework by registering simultaneously T 1 images and 65 fiber bundles consistently extracted in 12 subjects and compare it against non-linear T 1, tensor, and multi-modal T 1 + Fractional Anisotropy (FA) registration algorithms. Results show the superiority of the Log-domain Geometric Demons over their purely iconic counterparts.

Keywords

  • Registration
  • neural fibers
  • diffeomorphism
  • Demons Algorithm
  • intensity-base registration
  • tensor-base registration
  • log-domain

Download conference paper PDF

References

  1. Auzias, G., et al.: Diffeomorphic brain registration under exhaustive sulcal constraints. IEEE Trans. Med. Imaging (January 2011)

    Google Scholar 

  2. Avants, B.B., et al.: A reproducible evaluation of ants similarity metric performance in brain image registration. NeuroImage 54(3), 2033–2044 (2011)

    CrossRef  Google Scholar 

  3. Beg, M.F., et al.: Computing large deformation metric mappings via geodesic flows of diffeomorphisms. IJCV 61(2), 139–157 (2005)

    CrossRef  Google Scholar 

  4. Durrleman, S., et al.: Registration, atlas estimation and variability analysis of white matter fiber bundles modeled as currents. NeuroImage 55(3), 1073–1090 (2011)

    CrossRef  Google Scholar 

  5. Fillard, P., et al.: Clinical DT-MRI estimation, smoothing and fiber tracking with log-Euclidean metrics. IEEE Trans. Med. Imaging 26(11), 1472–1482 (2007)

    CrossRef  Google Scholar 

  6. Glaunès, J., et al.: Large deformation diffeomorphic metric curve mapping. IJCV 80, 317–336 (2008), 10.1007/s11263-008-0141-9

    CrossRef  Google Scholar 

  7. Guevara, P., et al.: Robust clustering of massive tractography datasets. Neuroimage 54(3), 1975–1993 (2011)

    CrossRef  Google Scholar 

  8. Ha, L., Prastawa, M., Gerig, G., Gilmore, J.H., Silva, C.T., Joshi, S.: Image Registration Driven by Combined Probabilistic and Geometric Descriptors. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part II. LNCS, vol. 6362, pp. 602–609. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  9. Poupon, C., et al.: A database dedicated to anatomo-functional study of human brain connectivity. In: 12th HBM Neuroimage, Florence, Italie, vol. 646 (2006)

    Google Scholar 

  10. Rueckert, D., Aljabar, P., Heckemann, R.A., Hajnal, J.V., Hammers, A.: Diffeomorphic Registration Using B-Splines. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4191, pp. 702–709. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  11. Siless, V., Guevara, P., Pennec, X., Fillard, P.: Joint T1 and Brain Fiber Diffeomorphic Registration Using the Demons. In: Liu, T., Shen, D., Ibanez, L., Tao, X. (eds.) MBIA 2011. LNCS, vol. 7012, pp. 10–18. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  12. Sotiras, A., Ou, Y., Glocker, B., Davatzikos, C., Paragios, N.: Simultaneous Geometric - Iconic Registration. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part II. LNCS, vol. 6362, pp. 676–683. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  13. Thirion, J.P.: Image matching as a diffusion process: an analogy with Maxwell’s demons. Medical Image Analysis 2(3), 243–260 (1998)

    CrossRef  Google Scholar 

  14. Vercauteren, T., Pennec, X., Perchant, A., Ayache, N.: Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 754–761. Springer, Heidelberg (2008)

    CrossRef  Google Scholar 

  15. Yeo, B., et al.: Dt-refind: Diffusion tensor registration with exact finite-strain differential. IEEE Trans. Med. Imaging 28(12), 1914–1928 (2009)

    CrossRef  Google Scholar 

  16. Yeo, B., et al.: Spherical demons: Fast diffeomorphic landmark-free surface registration. IEEE Trans. Med. Imaging 29(3), 650–668 (2010)

    CrossRef  MathSciNet  Google Scholar 

  17. Zhang, H., et al.: Deformable registration of diffusion tensor mr images with explicit orientation optimization. Medical Image Analysis 10(5), 764–785 (2006)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Parietal Team, INRIA Saclay-Île-de-France, Saclay, France

    Viviana Siless, Bertrand Thirion & Pierre Fillard

  2. CEA, DSV, I2BM, Neurospin bât 145, 91191, Gif-Sur-Yvette, France

    Viviana Siless, Jean-François Mangin, Cyril Poupon, Denis Le Bihan, Bertrand Thirion & Pierre Fillard

  3. MAP5, CNRS UMR 8145, Université Paris Descartes, 75006, Paris, France

    Joan Glaunès

  4. University of Concepción, Concepción, Chile

    Pamela Guevara

Authors
  1. Viviana Siless
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joan Glaunès
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pamela Guevara
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jean-François Mangin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cyril Poupon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Denis Le Bihan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Bertrand Thirion
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Pierre Fillard
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Project Team Asclepios, Inria Sophia Antipolis, 06902, Sophia-Antipolis, France

    Nicholas Ayache & Hervé Delingette & 

  2. MIT, CSAIL, 02139, Cambridge, MA, USA

    Polina Golland

  3. Information and Communication Headquarters, Nagoya University, 464-8603, Nagoya, Japan

    Kensaku Mori

Rights and permissions

Reprints and Permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Siless, V. et al. (2012). Joint T1 and Brain Fiber Log-Demons Registration Using Currents to Model Geometry. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33418-4_8

Download citation

  • .RIS
  • .ENW
  • .BIB
  • DOI: https://doi.org/10.1007/978-3-642-33418-4_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33417-7

  • Online ISBN: 978-3-642-33418-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Share this paper

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Search

Navigation

  • Find a journal
  • Publish with us

Discover content

  • Journals A-Z
  • Books A-Z

Publish with us

  • Publish your research
  • Open access publishing

Products and services

  • Our products
  • Librarians
  • Societies
  • Partners and advertisers

Our imprints

  • Springer
  • Nature Portfolio
  • BMC
  • Palgrave Macmillan
  • Apress
  • Your US state privacy rights
  • Accessibility statement
  • Terms and conditions
  • Privacy policy
  • Help and support

167.114.118.210

Not affiliated

Springer Nature

© 2023 Springer Nature