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Local White Matter Geometry Indices from Diffusion Tensor Gradients
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Institution: |
1Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA 2Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA 3Department of Computer Science, University of Chicago, Chicago, IL, USA |
Publisher: |
Int Conf Med Image Comput Comput Assist Interv. MICCAI 2009 |
Publication Date: |
Sep-2009 |
Citation: |
Int Conf Med Image Comput Comput Assist Interv. 2009;12(Pt 1):345–352. |
Appears in Collections: |
NA-MIC, NAC, NCIGT |
Sponsors: |
NIH R01 MH074794, R01 MH50740, K05 MH070047, P50 MH080272-01, P41 RR13218, U54 EB005149, U41 RR019703 Department of Veteran Affairs Merit Awards, VA Schizophrenia Center. |
Generated Citation: |
Savadjiev P, Kindlmann G, Bouix S, Shenton M, Westin C. Local White Matter Geometry Indices from Diffusion Tensor Gradients. Int Conf Med Image Comput Comput Assist Interv. 2009;12(Pt 1):345–352. |
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| Paper: | Download, View online |
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We introduce a framework for computing geometrical properties of white matter fibres directly from diffusion tensor fields. The key idea is to isolate the portion of the gradient of the tensor field corresponding to local variation in tensor orientation, and to project it onto a co-ordinate frame of tensor eigenvectors. The resulting eigenframe-centered representation makes it possible to define scalar geometrical measures that describe the underlying white matter fibres, directly from the diffusion tensor field and its gradient, without requiring prior tractography. We define two new scalar measures of (1) fibre dispersion and (2) fibre curving, and we demonstrate them on synthetic and in-vivo datasets. Finally, we illustrate their applicability in a group study on schizophrenia.
Additional Material
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Savadjiev-MICCAI2009-fig3.jpg (149.416kB)