Abstract
Current clinical and research neuroimaging protocols acquire images using multiple modalities, for instance, T1, T2, diffusion tensor and cerebral blood flow magnetic resonance images (MRI). These multivariate datasets provide unique and often complementary anatomical and physiological information about the subject of interest. We present a method that uses fused multiple modality (scalar and tensor) datasets to perform intersubject spatial normalization. Our multivariate approach has the potential to eliminate inconsistencies that occur when normalization is performed on each modality separately. Furthermore, the multivariate approach uses a much richer anatomical and physiological image signature to infer image correspondences and perform multivariate statistical tests. In this initial study, we develop the theory for Multivariate Symmetric Normalization (MVSyN), establish its feasibility and discuss preliminary results on a multivariate statistical study of 22q deletion syndrome.
Keywords
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.
Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Basser, P J, Mattiello, J., Le Bihan, D.: MR diffusion tensor specstroscopy and imaging. Biophys. J. 66, 259–267 (1994)
Wang, J., Licht, D.J., Jahng, G.H., Liu, C.S., Rabin, J.T., Haselgrove, J.C.: Pediatric perfusion imaging using pulsed arterial spin labeling. J. Mag. Reson. Imag. 18, 404–413 (2003)
Wang, J., Aguirre, G., Kimberg, D., Roc, A.C., Li, L., Detre, J.: Arterial spin labeling perfusion fmri with very low task frequency. Magn. Reson. Med. 49, 796–802 (2003)
Miller, M.I., Christensen, G.E., Amit, Y., Grenander, U.: Mathematical textbook of deformable neuroanatomies. Proc. Natl. Acad. Sci (USA) 90, 11944–11948 (1993)
Park, H.-J., Kubicki, M., Shenton, M E, et al.: Spatial normalization of diffusion tensor MRI using multiple channels. Neuroimage 20, 1995–2009 (2003)
Miller, M.I., Beg, M.F., Ceritoglu, C., Stark, C.: Increasing the power of functional maps of the medial temporal lobe by using large deformation diffeomorphic metric mapping. PNAS 102, 9685–9690 (2005)
Yan, C., Miller, M.I., Winslow, R.L., Younes, L.: Large deformation diffeomorphic metric mapping of vector fields. tmi 24, 1216–1230 (2005)
Zhang, H., Yushkevich, P.A., Alexander, D.C., Gee, J.C.: Deformable registration of diffusion tensor MR images with explicit orientation optimization. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3749, Springer, Heidelberg (2005)
Avants, B., Grossman, M., Gee, J.C.: Symmetric diffeomorphic image registration: Evaluating automated labeling of elderly and neurodegenerative cortex. Medical Image Analysis (in press online, 2007)
Alexander, D.C., Pierpaoli, C., Basser, P.J., Gee, J.C.: Spatial transformations of diffusion tensor magnetic resonance images. IEEE Trans. Med. Imaging 20, 1131–1139 (2001)
Avants, B., Gee, J.C.: Formulation and evaluation of variational curve matching with prior constraints. In: Gee, J.C., Maintz, J.B.A., Vannier, M.W. (eds.) Biomedical Image Registration, pp. 21–30. Springer, Heidelberg (2003)
Hermosillo, G., Chefd’Hotel, C., Faugeras, O.: A variational approach to multi-modal image matching. Intl. J. Comp. Vis. 50, 329–343 (2002)
Simon, T., Ding, L., Bish, J., McDonald-McGinn, D., Zackai, E., Gee, J.C.: Volumetric, connective, and morphologic changes in the brains of children with chromosome 22q11.2 deletion syndrome: an integrative study. Neuroimage 25, 169–180 (2005)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Avants, B., Duda, J.T., Zhang, H., Gee, J.C. (2007). Multivariate Normalization with Symmetric Diffeomorphisms for Multivariate Studies. In: Ayache, N., Ourselin, S., Maeder, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. MICCAI 2007. Lecture Notes in Computer Science, vol 4791. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75757-3_44
Download citation
DOI: https://doi.org/10.1007/978-3-540-75757-3_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75756-6
Online ISBN: 978-3-540-75757-3
eBook Packages: Computer ScienceComputer Science (R0)