Abstract
In this paper, we propose a large deformation diffeomorphic metric mapping algorithm to align multiple b-value diffusion weighted imaging (mDWI) data, specifically acquired via hybrid diffusion imaging (HYDI), denoted as LDDMM-HYDI. We adopt the work given in Hosseinbor et al. (2012) and represent the q-space diffusion signal with the Bessel Fourier orientation reconstruction (BFOR) signal basis. The BFOR framework provides the representation of mDWI in the q-space and thus reduces memory requirement. In addition, since the BFOR signal basis is orthonormal, the L 2 norm that quantifies the differences in q-space signals of any two mDWI datasets can be easily computed as the sum of the squared differences in the BFOR expansion coefficients. In this work, we show that the reorientation of the q-space signal due to spatial transformation can be easily defined on the BFOR signal basis. We incorporate the BFOR signal basis into the LDDMM framework and derive the gradient descent algorithm for LDDMM-HYDI with explicit orientation optimization. Using real HYDI datasets, we show that it is important to consider the variation of mDWI reorientation due to a small change in diffeomorphic transformation in the LDDMM-HYDI optimization.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alexander, D., Pierpaoli, C., Basser, P., Gee, J.: Spatial transformation of diffusion tensor magnetic resonance images. IEEE Trans. on Medical Imaging 20, 1131–1139 (2001)
Cetingul, H., Afsari, B., Vidal, R.: An algebraic solution to rotation recovery in hardi from correspondences of orientation distribution functions. In: 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 38–41 (May 2012)
Dhollander, T., Van Hecke, W., Maes, F., Sunaert, S., Suetens, P.: Spatial transformations of high angular resolution diffusion imaging data in Q-space. In: MICCAI CDMRI Workshop, pp. 73–83 (2010)
Dhollander, T., Veraart, J., Van Hecke, W., Maes, F., Sunaert, S., Sijbers, J., Suetens, P.: Feasibility and advantages of diffusion weighted imaging atlas construction in Q-space. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part II. LNCS, vol. 6892, pp. 166–173. Springer, Heidelberg (2011)
Dorst, L.: First order error propagation of the procrustes method for 3d attitude estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(2), 221–229 (2005)
Du, J., Goh, A., Qiu, A.: Diffeomorphic metric mapping of high angular resolution diffusion imaging based on riemannian structure of orientation distribution functions. IEEE Transactions on Medical Imaging 31(5), 1021–1033 (2012)
Du, J., Younes, L., Qiu, A.: Whole brain diffeomorphic metric mapping via integration of sulcal and gyral curves, cortical surfaces, and images. NeuroImage 56(1), 162–173 (2011)
Geng, X., Ross, T.J., Gu, H., Shin, W., Zhan, W., Chao, Y.P., Lin, C.P., Schuff, N., Yang, Y.: Diffeomorphic image registration of diffusion mri using spherical harmonics. IEEE Transactions on Medical Imaging 30(3), 747–758 (2011)
Hosseinbor, A.P., Chung, M.K., Wu, Y.C., Alexander, A.L.: Bessel fourier orientation reconstruction (bfor): An analytical diffusion propagator reconstruction for hybrid diffusion imaging and computation of q-space indices. NeuroImage 64, 650–670 (2013)
Hsu, Y.C., Hsu, C.H., Tseng, W.Y.I.: A large deformation diffeomorphic metric mapping solution for diffusion spectrum imaging datasets. NeuroImage 63(2), 818–834 (2012)
Raffelt, D., Tournier, J.D., Fripp, J., Crozier, S., Connelly, A., Salvado, O.: Symmetric diffeomorphic registration of fibre orientation distributions. NeuroImage 56(3), 1171–1180 (2011)
Wu, Y.C., Alexander, A.L.: Hybrid diffusion imaging. NeuroImage 36(3), 617–629 (2007)
Yap, P.T., Shen, D.: Spatial transformation of dwi data using non-negative sparse representation. IEEE Transactions on Medical Imaging 31(11), 2035–2049 (2012)
Yeo, B., Vercauteren, T., Fillard, P., Peyrat, J.M., Pennec, X., Golland, P., Ayache, N., Clatz, O.: Dt-refind: Diffusion tensor registration with exact finite-strain differential. IEEE Transactions on Medical Imaging 28(12), 1914–1928 (2009)
Zhang, P., Niethammer, M., Shen, D., Yap, P.-T.: Large deformation diffeomorphic registration of diffusion-weighted images. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part II. LNCS, vol. 7511, pp. 171–178. Springer, Heidelberg (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Du, J. et al. (2013). Diffeomorphic Metric Mapping of Hybrid Diffusion Imaging Based on BFOR Signal Basis. In: Gee, J.C., Joshi, S., Pohl, K.M., Wells, W.M., Zöllei, L. (eds) Information Processing in Medical Imaging. IPMI 2013. Lecture Notes in Computer Science, vol 7917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38868-2_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-38868-2_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38867-5
Online ISBN: 978-3-642-38868-2
eBook Packages: Computer ScienceComputer Science (R0)