Abstract
The diffusion tensor tractography has drawbacks such as low objectivity by interactive ROI setting and fiber-crossing. For coping with such problems, we are constructing a statistical atlas of white matter fiber tracts, in which probability density maps of tract structures are stored with diffusion tensor parameters on spatially normalized brain data. In building the atlas, our fiber tract modeling method plays a key role, which is based on a novel approach of vector/tensor field reconstruction avoiding fiber-crossings. In this abstract, we describe the modeling method, our statistical atlas, and the preliminary results.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Mori, S., Crain, B.J., et al.: Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann. Neurol. 45, 265–269 (1999)
Conturo, T.E., Lori, N.F., Cul, T.S., et al.: Tracking neuronal fiber pathways in the living human brain. Proc. Natl. Acad. Sci. 96, 10422–10427 (1999)
Basser, P.J., Pajevic, S., Pierpaoli, C., et al.: In Vivo Fiber Tractography Using DT-MRI Data. Magnetic Resonance in Medicine 44, 625–632 (2000)
Mori, S., van Zijl, P.C.M.: Fiber Tracking: Principles and Strategies – A Technical Review. NMR Biomed. 15, 468–480 (2002)
Jones, D.K., et al.: Spatial Normalization and Averaging of Diffusion Tensor MRI Data Sets. NeuroImage 17, 592–617 (2002)
Park, H.J., et al.: Spatial normalization of diffusion tensor MRI using multiple channels. NeuroImage 20, 1995–2009 (2003)
Wakana, S., et al.: Fiber Tract–based Atlas of Human White Matter Anatomy. Radiology 230, 77–87 (2004)
Corouge, I., et al.: A Statistical Shape Model of Individual Fiber Tracts Extracted from Diffusion Tensor MRI. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3217, pp. 671–679. Springer, Heidelberg (2004)
Masutani, Y., Aoki, S., et al.: RBF-based reconstruction of fiber orientation vector field for white matter fiber tract modeling. In: Proc. of ISMRM 2004 (2004)
Globus, A., et al.: A tool for visualizing the topology of three-dimensional vector fields. In: Proc. of the 2nd conference on Visualization 1991, pp. 33–40 (1991)
Helman, J.L., Hesselink, L.: Visualization of Vector Field Topology in Fluid Flows. IEEE CG&A 11(3), 36–46 (1991)
Ashburner, J., Friston, K.J.: Nonlinear spatial normalization using basis functions. Hum. Brain Mapp. 7(4), 254–266 (1999)
Taguchi, G., Jugulum, R.: The Mahalanobis-Taguchi Strategy: A Pattern Technology System. John Wiley & Sons, Chichester (2002)
Kamada, K., Morita, A., Masutani, Y., et al.: Combined utilization of tractography-integrated functional neuronavigation and direct fiber stimulation. Journal of Neurosurgery 202(4), 664–672 (2005)
Maruyama, K., Kamada, K., Aoki, S., et al.: Integration of three-dimensional corticospinal tractography in treatment planning of gamma-knife radiosurgery. Journal of Neurosurgery 202(4), 673–677 (2005)
Jones, D.K., Horsfield, M.A., Simmons, A.: Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magnetic Resonance in Medicine 42, 515–525 (1999)
Hesselink, L., et al.: The Topology of Symmetric, Second-Order 3D Tensor Fields. IEEE trans. visualization and CG 3(1), 1–11 (1997)
Donnell, L.O., Grimson, W.E.L., Westin, C.F.: Interface Detection in Diffusion Tensor MRI. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 360–367. Springer, Heidelberg (2004)
Brun, A., Knutsson, H., et al.: Clustering Fiber Traces Using Normalized Cuts. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 368–375. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Masutani, Y. et al. (2005). Building Statistical Atlas of White Matter Fiber Tract Based on Vector/Tensor Field Reconstruction in Diffusion Tensor MRI. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_11
Download citation
DOI: https://doi.org/10.1007/11595755_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30750-1
Online ISBN: 978-3-540-32284-9
eBook Packages: Computer ScienceComputer Science (R0)