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Publication Detail
Quantification of the shape of fiber tracts
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Batchelor PG, Calamante F, Tournier J-D, Atkinson D, Hill DL, Connelly A
  • Publication date:
    2006
  • Pagination:
    894, 903
  • Journal:
    MAGN RESON MED
  • Volume:
    55
  • Issue:
    4
  • Print ISSN:
    0740-3194
  • Keywords:
    fiber tracts, OF, QUANTIFICATION, rcs, SHAPE, THE, TRACT
Abstract
The fiber tracts generated using diffusion MRI are usually simplydisplayed and assessed visually for a specific clinical ormedical research purpose. This paper proposes computationaltechniques that can be used to study the shape of the tracts andmake interindividual comparisons. These methods make use offundamental geometric invariants, such as curvatures and torsions,or Fourier descriptors, together with the link of a pair ofcurves. Intersubject comparisons only require that the startingand ending points of the tracts can be defined and do notrequire point-by-point correspondences such as obtained usingimage registration. Principal component analysis-basedshape analysis is also investigated. The invariants are tested onsimulations and in vivo datasets, and the scale dependence andnoise sensitivity of the measures are assessed. The potentialfor these techniques to be used in neuroscience research andclinical applications is demonstrated. The fiber tracts generated using diffusion MRI are usually simplydisplayed and assessed visually for a specific clinical ormedical research purpose. This paper proposes computationaltechniques that can be used to study the shape of the tracts andmake interindividual comparisons. These methods make use offundamental geometric invariants, such as curvatures and torsions,or Fourier descriptors, together with the link of a pair ofcurves. Intersubject comparisons only require that the startingand ending points of the tracts can be defined and do notrequire point-by-point correspondences such as obtained usingimage registration. Principal component analysis-basedshape analysis is also investigated. The invariants are tested onsimulations and in vivo datasets, and the scale dependence andnoise sensitivity of the measures are assessed. The potentialfor these techniques to be used in neuroscience research andclinical applications is demonstrated.
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Metabolism & Experi Therapeutics
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