Towards a shape model of white matter fiber bundles using diffusion
tensor MRI
Biomedical Imaging: Macro to Nano, 2004. IEEE International Symposium
on, page 344--347Vol.1. (15-18 April 2004)DOI: 10.1109/ISBI.2004.1398545
Abstract
White matter fiber bundles of the human brain form a spatial pattern
defined by the anatomical and functional architecture. Human brain
atlases provide names for individual tracts and document that these
patterns are comparable across subjects. Tractography applied to
the tensor field in diffusion tensor imaging (DTI) results in sets
of streamlines which can be associated with major fiber tracts.
Comparison of fiber tract properties across subjects requires comparison
at corresponding anatomical locations. As an alternative to linear
and nonlinear registration of DTI images and voxel-based analysis,
we propose a novel methodology that models the shape of white matter
tracts. A clustering uses similarity of adjacent curves and an iterative
processing scheme to group sets of curves to bundles and to reject
outliers. Unlike previous work which models fiber tracts as sets
of curves centered around a spine, we extend the notion of bundling
towards a more general representation of manifolds. We describe
tracts, represented as sets of curves of similar shape, by a shape
prototype swept along a space trajectory. This approach can naturally
describe white matter structures observed either as bundles dispersing
towards the cortex or tracts defined as dense patterns of parallel
fibers forming manifolds. Curves are parameterized by arc-length
and represented by intrinsic local shape properties (curvature and
torsion). Feasibility is demonstrated by modeling the left and right
cortico-spinal tracts and a part of the transversal callosal tract.
Description
Diffusion Tensor Imaging (DTI)
