Abstract:
Diffusion weighted magnetic resonance imaging (DW MRI) is a technique
that measures the diffusion properties of water molecules to produce a
tensor-valued volume dataset. Because water molecules can diffuse more
easily along fiber tracts, for example in the brain, rather than
across them, diffusion is anisotropic and can be used for
segmentation. Segmentation requires the identification of regions with
different diffusion properties. In this paper we propose a new set of
rotationally invariant diffusion measures which may be used to map the
tensor data into a scalar representation. Our invariants may be
rapidly computed because they do not require the calculation of
eigenvalues. We use these invariants to analyze a 3D DW MRI scan of a
human head and build geometric models corresponding to isotropic and
anisotropic regions. We then utilize the models to perform
quantitative analysis of these regions, for example calculating their
surface area and volume.