Abstract
We develop an algorithm for brain connectivity assessment using geodesics in HARDI (high angular resolution diffusion imaging). We propose to recast the problem of finding fibers bundles and connectivity maps to the calculation of shortest paths on a Riemannian manifold defined from fiber ODFs computed from HARDI measurements. Several experiments on real data show that our method is able to segment fibers bundles that are not easily recovered by other existing methods.
Chapter PDF
Similar content being viewed by others
Keywords
- Riemannian Manifold
- Fractional Anisotropy
- Orientation Distribution Function
- Brain Connectivity
- Superior Longitudinal Fasciculus
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Jansons, K.M., Alexander, D.C.: Persistent angular structure: new insights fom diffusion magnetic resonance imaging data. Inverse Problems 19, 1031–1046 (2003)
Tournier, J.D., 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)
Jian, B., Vemuri, B.C.: A unified computational framework for deconvolution to reconstruct multiple fibers from diffusion weighted MRI. IEEE Transactions on Medical Imaging 26(11), 1464–1471 (2007)
Descoteaux, M., Deriche, R., Knösche, T.R., Anwander, A.: Deterministic and probabilistic tractography based on complex fibre orientation distributions. IEEE Transactions in Medical Imaging 28(2), 269–286 (2009)
Kreher, B.W., Schneider, J.F., Mader, J., Martin, E., Hennig, J., Il’yasov, K.A.: Multitensor approach for analysis and tracking of complex fiber configurations. Magnetic Resonance in Medicine 54, 1216–1225 (2005)
Bergmann, Ø., Kindlmann, G., Peled, S., Westin, C.F.: Two-tensor fiber tractography. In: ISBI, Arlington, Virginia, USA, pp. 796–799 (2007)
Wedeen, V., Wang, R., Schmahmann, J., Benner, T., Tseng, W., Dai, G., Pandya, D., Hagmann, P., D’Arceuil, H., de Crespigny, A.: Diffusion spectrum magnetic resonance imaging (dsi) tractography of crossing fibers. Neuroimage 41(4), 1267–1277 (2008)
Parker, G.J.M., Alexander, D.C.: Probabilistic anatomical connectivity derived from the microscopic persistent angular structure of cerebral tissue. Philosophical Transactions of the Royal Society, Series B 360, 893–902 (2005)
Perrin, M., Poupon, C., Cointepas, Y., Rieul, B., Golestani, N., Pallier, C., Riviere, D., Constantinesco, A., Bihan, D.L., Mangin, J.F.: Fiber tracking in q-ball fields using regularized particle trajectories. In: Christensen, G.E., Sonka, M. (eds.) IPMI 2005. LNCS, vol. 3565, pp. 52–63. Springer, Heidelberg (2005)
Seunarine, K.K., Cook, P.A., Embleton, K., Parker, G.J.M., Alexander, D.C.: A general framework for multiple-fibre pico tractography. In: Medical Image Understanding and Analysis (2006)
Behrens, T.E.J., Johansen-Berg, H., Jbabdi, S., Rushworth, M.F.S., Woolrich, M.W.: Probabilistic diffusion tractography with multiple fibre orientations. what can we gain? Neuroimage 34(1), 144–155 (2007)
Savadjiev, P., Campbell, J.S.W., Descoteaux, M., Deriche, R., Pike, G.B., Siddiqi, K.: Labeling of ambiguous sub-voxel fibre bundle configurations in high angular resolution diffusion MRI. Neuroimage 41(1), 58–68 (2008)
Zhang, F., Hancock, E.R., Goodlett, C., Gerig, G.: Probabilistic white matter fiber tracking using particle filtering and von mises-fisher sampling. Medical Image Analysis 13(1), 5–18 (2008)
Melonakos, J., Mohan, V., Niethammer, M., Smith, K., Kubicki, M., Tannenbaum, A.: Finsler tractography for white matter connectivity analysis of the cingulum bundle. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part I. LNCS, vol. 4791, pp. 36–43. Springer, Heidelberg (2007)
Lenglet, C., Prados, E., Pons, J., Deriche, R., Faugeras, O.: Brain connectivity mapping using riemannian geometry, control theory and pdes. SIAM Journal on Imaging Sciences 2(2), 285–322 (2009)
Jbabdi, S., Bellec, P., Toro, R., Daunizeau, J., Pelegrini-Issac, M., Benali, H.: Accurate anisotropic fast marching for diffusion-based geodesic tractography. International Journal of Biomedical Imaging, 1–12 (2008)
Jonasson, L., Bresson, X., Hagmann, P., Thiran, J., Wedeen, V.: Representing Diffusion MRI in 5D Simplifies Regularization and Segmentation of White Matter Tracts. IEEE Transactions on Medical Imaging 26, 1547–1554 (2007)
Sethian, J.A.: Level Set Methods and Fast Marching Methods. Cambridge University Press, Cambridge (1999)
Deschamps, T., Cohen, L.: Fast extraction of minimal paths in 3D images and applications to virtual endoscopy. Medical Image Analysis 5(4), 281–299 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Péchaud, M., Descoteaux, M., Keriven, R. (2009). Brain Connectivity Using Geodesics in HARDI. In: Yang, GZ., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009. MICCAI 2009. Lecture Notes in Computer Science, vol 5762. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04271-3_59
Download citation
DOI: https://doi.org/10.1007/978-3-642-04271-3_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04270-6
Online ISBN: 978-3-642-04271-3
eBook Packages: Computer ScienceComputer Science (R0)