Abstract
A methodology is presented for estimation of a probability density function of cerebral fibre orientations when one or two fibres are present in a voxel. All data are acquired on a clinical MR scanner, using widely available acquisition techniques. The method models measurements of water diffusion in a single fibre by a Gaussian density function and in multiple fibres by a mixture of Gaussian densities. The effects of noise on complex MR diffusion weighted data are explicitly simluated and parameterised. This information is used for standard and Monte Carlo streamline methods. Deterministic and probabilistic maps of anatomical voxel scale connectivity between brain regions are generated.
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Alexander, A.L., Hasan, K.M., Mariana, L., Tsuruda, J.S., Parker, D.L.: Analysis of partial volume effects in diffusion-tensor MRI. Magn. Reson. Med. 45, 770–780 (2001)
Alexander, D.C., Barker, G.J., Arridge, S.R.: Detection and modelling of non- Gaussian apparent diffusion coefficient profiles in human brain data. Magn. Reson. Med. 48, 331–340 (2002)
Behrens, T.E.J., Jenkinson, M., Brady, J.M., Smith, S.M.: A probabilistic framework for estimating neural connectivity from diffusion weighted MRI. Proc. Int. Soc. Magn. Reson. Med, 1142 (2002)
Conturo, T.E., Lori, N.F., Cull, T.S., Akbudak, E., Snyder, A.Z., Shimony, J.S., McKinstry, R.C., Burton, H., Raichle, M.E.: Tracking neuronal fiber pathways in the living human brain. Proc. Nat. Acad. Sci. USA 96, 10422–10427 (1999)
Frank, L.R.: Characterization of anisotropy in high angular resolution diffusionweighted MRI. Magn. Reson. Med. 47, 1083–1099 (2002)
Jones, D.K., Horsfield, M.A., Simmons, A.: Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 42, 515–525 (1999)
Jones, D.K.: Determining and visualizing uncertainty in estimates of fiber orientation from diffusion tensor MRI. Magn. Reson Med. 49, 7–12 (2003)
Koch, M.A., Norris, D.G., Hund-Georgiadis, M.: An investigation of functional and anatomical connectivity using magnetic resonance imaging. NeuroImage 16, 241–250 (2002)
Lazar, M., Alexander, A.L.: White matter tractography using random vector (RAVE) perturbation. In: Proc. Int. Soc. Magn. Reson. Med., p. 539 (2002)
Parker, G.J.M., Barker, G.J., Buckley, D.L.: A probabilistic index of connectivity (PICo) determined using a Monte Carlo approach to streamlines. In: ISMRM Workshop on Diffusion MRI (Biophysical Issues), Saint-Malo, France, pp. 245–255 (2002)
Parker, G.J.M., Barker, G.J., Thacker, N.A., Jackson, A.: A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of anisotropic diffusion. In: Proc. Int. Soc. Magn. Reson. Med., p. 1165 (2002)
Pierpaoli, C., Basser, P.J.: Toward a quantitative assessment of diffusion anisotropy. Magn. Reson. Med. 36, 893–906 (1996)
Stejskal, E.O., Tanner, J.E.: Spin diffusion measurements: spin echoes in the presence of a time-dependent field gradient. J. Chem. Phys. 42, 288–292 (1965)
Symms, M.R., Barker, G.J., Franconi, F., Clark, C.A.: Correction of eddy-current distortions in diffusion-weighted echo-planar images with a two-dimensional registration technique. In: Proc. Int. Soc. Magn. Reson. Med., p. 1723 (1997)
Tuch, D.S., Wiegell, M.R., Reese, T.G., Belliveau, J.W., Weeden, V.J.: Measuring cortico-cortical connectivity matrices with diffusion spectrum imaging. In: Proc. Int. Soc. Magn. Reson. Med., p. 502 (2001)
Wheeler-Kingshott, C.A.M., Boulby, P.A., Symms, M.R., Barker, G.J.: Optimised cardiac gating for high angular-resolution whole-brain DTI on a standard scanner. In: Proc. Int. Soc. Magn. Reson. Med., p. 1118 (2002)
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Parker, G.J.M., Alexander, D.C. (2003). Probabilistic Monte Carlo Based Mapping of Cerebral Connections Utilising Whole-Brain Crossing Fibre Information. In: Taylor, C., Noble, J.A. (eds) Information Processing in Medical Imaging. IPMI 2003. Lecture Notes in Computer Science, vol 2732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45087-0_57
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DOI: https://doi.org/10.1007/978-3-540-45087-0_57
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