In this paper we develop a new technique for tracing anatomical fibers
from 3D tensor fields. The technique extracts salient tensor features
using a local regularization technique that allows the algorithm to
cross noisy regions and bridge gaps in the data. We applied the method
to human brain DT-MRI data and recovered identifiable anatomical
structures that correspond to the white matter brain-fiber
pathways. The images in this paper are derived from a dataset having
x
x
resolution. We were able to recover fibers with less
than the voxel size resolution by applying the regularization technique,
i.e., using a priori assumptions about fiber smoothness. The
regularization procedure is done through a moving least squares filter
directly incorporated in the tracing algorithm.
