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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 |
Volume Number: |
12 |
Issue Number: |
Pt 1 |
Pages: |
345-352 |
Citation: |
Int Conf Med Image Comput Comput Assist Interv. 2009;12(Pt 1):345–352. |
PubMed ID: |
20426006 |
PMCID: |
PMC2892818 |
Keywords: |
Diffusion Tensor Imaging, Magnetic Resonance Imaging, Fibre Geometry, Rotation Tangents, Fibre Dispersion, Fibre Curving, Schizophrenia |
Appears in Collections: |
NA-MIC, LMI, NAC, NCIGT, PNL |
Sponsors: |
K05 MH070047/MH/NIMH NIH HHS/United States P41 RR13218/RR/NCRR NIH HHS/United States P50 MH080272-01/MH/NIMH NIH HHS/United States R01 MH074794/MH/NIMH NIH HHS/United States R01 MH50740/MH/NIMH NIH HHS/United States U41 RR019703/RR/NCRR NIH HHS/United States U54 EB005149/EB/NIBIB NIH HHS/United States |
Generated Citation: |
Savadjiev P., Kindlmann G.L., Bouix S., Shenton M.E., Westin C-F. Local White Matter Geometry Indices from Diffusion Tensor Gradients. Int Conf Med Image Comput Comput Assist Interv. 2009;12(Pt 1):345–352. PMID: 20426006. PMCID: PMC2892818. |
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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
1 File (149.416kB)
Savadjiev-MICCAI2009-fig3.jpg (149.416kB)