Segmentation of Q-Ball Images Using Statistical Surface Evolution

  • Maxime Descoteaux
  • Rachid Deriche
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4792)


In this article, we develop a new method to segment Q-Ball imaging (QBI) data. We first estimate the orientation distribution function (ODF) using a fast and robust spherical harmonic (SH) method. Then, we use a region-based statistical surface evolution on this image of ODFs to efficiently find coherent white matter fiber bundles. We show that our method is appropriate to propagate through regions of fiber crossings and we show that our results outperform state-of-the-art diffusion tensor (DT) imaging segmentation methods, inherently limited by the DT model. Results obtained on synthetic data, on a biological phantom, on real datasets and on all 13 subjects of a public QBI database show that our method is reproducible, automatic and brings a strong added value to diffusion MRI segmentation.


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  1. 1.
    Zhukov, L., Museth, K., Breen, D., Whitakert, R., Barr, A.H.: Level set modeling and segmentation of DT-MRI brain data. J. of Electronic Imaging 12, 125–133 (2003)CrossRefGoogle Scholar
  2. 2.
    Feddern, C., Weickert, J., Burgeth, B.: Level-set methods for tensor-valued images. In: Proceedings of the Second IEEE Workshop on Geometric and Level Set Methods in Computer Vision, pp. 65–72. IEEE Computer Society Press, Los Alamitos (2003)Google Scholar
  3. 3.
    Wang, Z., Vemuri, B.C.: DTI segmentation using an information theoretic tensor dissimilarity measure. IEEE Trans. in Medical Imaging 24(10), 1267–1277 (2005)CrossRefGoogle Scholar
  4. 4.
    Jonasson, L.: Segmentation of diffusion weighted MRI using the level set framework. PhD thesis, Ecole Polytechnique federale de Lausanne (2006)Google Scholar
  5. 5.
    Lenglet, C., Rousson, M., Deriche, R.: DTI segmentation by statistical surface evolution. IEEE Transactions in Medical Imaging 25(6), 685–700 (2006)CrossRefMathSciNetGoogle Scholar
  6. 6.
    Tuch, D.: Q-ball imaging. Magnetic Resonance in Medicine 52(6), 1358–1372 (2004)CrossRefGoogle Scholar
  7. 7.
    McGraw, T., Vemuri, B., Yezierski, R., Mareci, T.: Segmentation of high angular resolution diffusion MRI modeled as a field of von Mises-Fisher mixtures. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3953, pp. 463–475. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Descoteaux, M., Angelino, E., Fitzgibbons, S., Deriche, R.: Regularized, fast, and robust analytical Q-ball imaging. Magnetic Resonance in Medicine (to appear)Google Scholar
  9. 9.
    Poupon, C., Poupon, F., Allirol, L., Mangin, J.F.: A database dedicated to anatomo-functional study of human brain connectivity. In: HBM. Twelfth Annual Meeting of the Organization for Human Brain Mapping (2006)Google Scholar
  10. 10.
    Anderson, A.: Measurements of fiber orientation distributions using high angular resolution diffusion imaging. Magnetic Resonance in Medicine 54, 1194–1206 (2005)CrossRefGoogle Scholar
  11. 11.
    Hess, C., Mukherjee, P., Han, E., Xu, D., Vigneron, D.: Q-ball reconstruction of multimodal fiber orientations using the spherical harmonic basis. Magnetic Resonance in Medicine 56, 104–117 (2006)CrossRefGoogle Scholar
  12. 12.
    Paragios, N., Deriche, R.: Geodesic active regions: a new paradigm to deal with frame partition problems in computer vision. Journal of Visual Communication and Image Representation 13(1/2), 249–268 (2002)CrossRefGoogle Scholar
  13. 13.
    Campbell, J., Siddiqi, K., Rymar, V., Sadikot, A., Pike, B.: Flow-based fiber tracking with diffusion tensor Q-ball data: Validation and comparison to principal diffusion direction techniques. NeuroImage 27(4), 725–736 (2005)CrossRefGoogle Scholar
  14. 14.
    Anwander, A., Tittgemeyer, M., von Cramon, D.Y., Friederici, A.D., Knosche, T.R.: Connectivity-based parcellation of BROCA’s area. Cerebral Cortex 17(4), 816–825 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Maxime Descoteaux
    • 1
  • Rachid Deriche
    • 1
  1. 1.Odyssée Project Team, INRIA/ENS/ENPC, INRIA Sophia AntipolisFrance

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