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Delineating White Matter Structure in Diffusion Tensor MRI with Anisotropy Creases
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Institution: |
1Laboratory of Mathematics in Imaging, Department of Radiology, Harvard Medical School, USA. gk@bwh.harvard.edu 2Computer Science Department, Purdue University |
Publisher: |
Med Image Anal |
Publication Date: |
Oct-2007 |
Volume Number: |
11 |
Issue Number: |
5 |
Pages: |
492-502 |
Citation: |
Med Image Anal. 2007 Oct;11(5):492-502. |
PubMed ID: |
17804278 |
PMCID: |
PMC2367700 |
Keywords: |
Diffusion Tensor MRI, Anisotropy, Ridges and valleys, Crease surface extraction, White matter geometry |
Appears in Collections: |
LMI, NAC, NCIGT |
Sponsors: |
P41 RR12553-07 (RR) funded by NCRR P41 RR13218 (RR) funded by NCRR P41 RR15241-01A1 (RR) funded by NCRR R01 AG20012-01 (AG) funded by NIA R01 MH050740 (MH) funded by NIMH R01 MH074794 (MH) funded by NIMH T32 EB002177 (EB) funded by NIBIB U41 RR019703 (RR) funded by NCRR |
Generated Citation: |
Kindlmann G., Tricoche X., Westin C-F. Delineating White Matter Structure in Diffusion Tensor MRI with Anisotropy Creases. Med Image Anal. 2007 Oct;11(5):492-502. PMID: 17804278. PMCID: PMC2367700. |
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Geometric models of white matter architecture play an increasing role in neuroscientific applications of diffusion tensor imaging, and the most popular method for building them is fiber tractography. For some analysis tasks, however, a compelling alternative may be found in the first and second derivatives of diffusion anisotropy. We extend to tensor fields the notion from classical computer vision of ridges and valleys, and define anisotropy creases as features of locally extremal tensor anisotropy. Mathematically, these are the loci where the gradient of anisotropy is orthogonal to one or more eigenvectors of its Hessian. We propose that anisotropy creases provide a basis for extracting a skeleton of the major white matter pathways, in that ridges of anisotropy coincide with interiors of fiber tracts, and valleys of anisotropy coincide with the interfaces between adjacent but distinctly oriented tracts. The crease extraction algorithm we present generates high-quality polygonal models of crease surfaces, which are further simplified by connected-component analysis. We demonstrate anisotropy creases on measured diffusion MRI data, and visualize them in combination with tractography to confirm their anatomic relevance.
Additional Material
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Kindlmann-MedIA2007-fig5.jpg (174.325kB)