Abstract
This paper presents processing and visualization techniques for Diffusion
Tensor Magnetic Resonance Imaging (DT-MRI). In DT-MRI, each voxel
is assigned a tensor that describes local water diffusion. The geometric
nature of diffusion tensors enables us to quantitatively characterize
the local structure in tissues such as bone, muscle, and white matter
of the brain. This makes DT-MRI an interesting modality for image
analysis. In this paper we present a novel analytical solution to
the Stejskal-Tanner diffusion equation system whereby a dual tensor
basis, derived from the diffusion sensitizing gradient configuration,
eliminates the need to solve this equation for each voxel. We further
describe decomposition of the diffusion tensor based on its symmetrical
properties, which in turn describe the geometry of the diffusion
ellipsoid. A simple anisotropy measure follows naturally from this
analysis. We describe how the geometry or shape of the tensor can
be visualized using a coloring scheme based on the derived shape
measures. In addition, we demonstrate that human brain tensor data
when filtered can effectively describe macrostructural diffusion,
which is important in the assessment of fiber-tract organization.
We also describe how white matter pathways can be monitored with
the methods introduced in this paper. DT-MRI tractography is useful
for demonstrating neural connectivity (in vivo) in healthy and diseased
brain tissue.
- 12044998
- and
- brain,
- computer-assisted,
- data
- display,
- gov't,
- humans,
- image
- imaging,
- magnetic
- models,
- non-u.s.
- p.h.s.,
- processing,
- research
- resonance
- sensitivity
- specificity,
- support,
- theoretical,
- u.s.
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