Abstract
Orientation probability density transform (OPDT) is a single-shell high angular resolution diffusion imaging (HARDI) estimator proposed by Tristán-Vega et al. for orientation probability density function (OPDF), i.e. marginal orientation distribution function (ODF) of white matter fibers in the brain. Unlike ODF in Q-Ball imaging (QBI), the Jacobian of the spherical coordinate is included in OPDF. OPDT is based on the Funk-Radon transform (FRT), so there is blurring introduced by FRT. Aganj et al. have proved that the radial part of the OPDF equals a constant, which is independent of the diffusion signal. With this consideration, we propose an improved form of OPDT with a closed form expression, which can reduce the FRT blurring in OPDT by replacing the radial part (a non-constant function) with its mean value over the sphere. Compared with OPDT, the proposed FRT-based single-shell HARDI estimator improves the angular resolution, and almost maintains the higher angular accuracy, robustness to noise and computational efficiency. Results on synthetic data and real human brain data are provided to demonstrate the effectiveness of the proposed model.
Similar content being viewed by others
References
Beaulieu, C.: The basis of anisotropic water diffusion in the nervous system—a technical review. NMR Biomed. 15(7–8), 435–455 (2002)
Bammer, R.: Basic principles of diffusion-weighted imaging. Eur. J. Radiol. 45(3), 169–184 (2003)
Basser, P.J., Mattiello, J., LeBihan, D.: Estimation of the effective self-diffusion tensor from the NMR spin echo. J. Magn. Reson., Ser. B 103(3), 247–254 (1994)
Le Bihan, D., Mangin, J.F., Poupon, C., Clark, C.A., Pappata, S., Molko, N., Chabriat, H.: Diffusion tensor imaging: concepts and applications. J. Magn. Reson. Imaging 13(4), 534–546 (2001)
Mori, S., Zhang, J.: Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51(5), 527–539 (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)
Wedeen, V.J., Reese, T.G., Tuch, D.S., Weigel, M.R., Dou, J.-G., Weiskoff, R.M., Chessler, D.: Mapping fiber orientation spectra in cerebral white matter with Fourier-transform diffusion MRI. In: Proc. of the 8th ISMRM, Denver, p. 82 (2000)
Tuch, D.S., Reese, T.G., Wiegell, M.R., Makris, N., Belliveau, J.W., Wedeen, V.J.: High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn. Reson. Med. 48(4), 577–582 (2002)
Tuch, D.S.: Diffusion MRI of complex tissue structure. Ph.D. thesis, Harvard University and Massachusetts Institute of Technology (2002)
Descoteaux, M., Deriche, R., Le Bihan, D., Mangin, J.-F., Poupon, C.: Diffusion propagator imaging: using Laplaces equation and multiple shell acquisitions to reconstruct the diffusion propagator. In: Information Processing in Medical Imaging (IPMI), pp. 1–13. Springer, Berlin (2009)
Descoteaux, M., Deriche, R., Le Bihan, D., Mangin, J.-F., Poupon, C.: Multiple q-shell diffusion propagator imaging. Med. Image Anal. 15(4), 603–621 (2011)
Tuch, D.S.: Q-Ball imaging. Magn. Reson. Med. 52(6), 1358–1372 (2004)
Wedeen, V.J., Hagmann, P., Tseng, W.Y., Reese, T.G., Weisskoff, R.M.: Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn. Reson. Med. 54(6), 1377–1386 (2005)
Tristán-Vega, A., Westin, C.-F., Aja-Fernández, S.: Estimation of fiber orientation probability density functions in high angular resolution diffusion imaging. Neuroimage 47(2), 638–650 (2009)
Anderson, A.W.: Measurement of fiber orientation distributions using high angular resolution diffusion imaging. Magn. Reson. Med. 54(5), 1194–1206 (2005)
Hess, C.P., Mukherjee, P., Han, E.T., Xu, D., Vigneron, D.B.: Q-ball reconstruction of multimodal fiber orientations using the spherical harmonic basis. Magn. Reson. Med. 56(1), 104–117 (2006)
Descoteaux, M., Angelino, E., Fitzgibbons, S., Deriche, R.: A fast and robust ODF estimation algorithm in q-ball imaging. In: IEEE International Symposium on Biomedical Imaging (ISBI), Arlington, Virginia, USA, pp. 81–84 (2006)
Descoteaux, M., Angelino, E., Fitzgibbons, S., Deriche, R.: Regularized, fast, and robust analytical q-ball imaging. Magn. Reson. Med. 58(3), 497–510 (2007)
Lenglet, C., Campbell, J.S.W., Descoteaux, M., Haro, G., Savadjiev, P., Wassermann, D., Anwander, A., Deriche, R., Pike, G.B., Sapiro, G.: Mathematical methods for diffusion MRI processing. Neuroimage 45(1), S111–S122 (2009)
Aganj, I., Lenglet, C., Sapiro, G.: ODF reconstruction in q-ball imaging with solid angle consideration. In: Proceeding of the 6th International Symposium on Biomedical Imaging: from Nano to Macro (ISBI), pp. 1398–1401 (2009)
Tristán-Vega, A., Westin, C.-F., Aja-Fernández, S.: A new methodology for the estimation of fiber populations in the white matter of the brain with the Funk-Radon transform. Neuroimage 49(2), 1301–1315 (2010)
Alexander, D., Barker, G., Arridge, S.: Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data. Magn. Reson. Med. 48(2), 331–340 (2002)
Frank, L.R.: Characterization of anisotropy in high angular resolution diffusion-weighted MRI. Magn. Reson. Med. 47(6), 1083–1099 (2002)
Descoteaux, M., Angelino, E., Fitzgibbons, S., Deriche, R.: Apparent diffusion coefficients from high angular resolution diffusion imaging: estimation and applications. Magn. Reson. Med. 56(2), 395–410 (2006)
Özarslan, E., Shepherd, T.M., Vemuri, B.C., Blackband, S.J., Mareci, T.H.: Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT). Neuroimage 31(3), 1086–1103 (2006)
Anderson, A., Ding, Z.: Sub-voxel measurement of fiber orientation using high angular resolution diffusion tensor imaging. In: Proceedings of the 10th Annual Meeting of ISMRM, p. 440 (2002)
Tournier, J., Calamante, F., Gadian, D.G., Connelly, A.: Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage 23(3), 1176–1185 (2004)
Tournier, J., 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)
Acknowledgements
The authors are sincerely grateful to all the anonymous reviewers for valuable comments and suggestions that have considerably improved the manuscript. The authors would like to thank Professor Ching-Po Lin for providing the human brain dataset. This work was supported by grants from the National Basic Research Program of China (973 program, 2011CB707800) and the National Natural Science Foundation of China (91132301 and 11171300).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, N., Li, C. & Jiang, T. An improved OPDT model in high angular resolution diffusion imaging. J Math Imaging Vis 48, 385–395 (2014). https://doi.org/10.1007/s10851-012-0412-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10851-012-0412-5