RESUMEN
A fundamental
problem in medical imaging is to transport
an atlas associated with a template image onto new
data. This is sometimes achieved by registering (warping) the template to
the data and using the induced
(spatial) deformation field to impose
an atlas on the data.There are a number of alignment
techniques which bring two images
in register; however, few studies have
been done to quantitatively compare various warping methods. In this paper we
compare different wavelet space thresholding schemes (uniform, spatially, and frequency adaptive, Bayesian) and develop
two approaches for quantitative evaluation of the
performance of three nonaffine warping techniques and one affine
polynomial (12 parameter) registration on groups of data. The results of
the affine and nonaffine warps
are evaluated, both on structural magnetic
resonance imaging (MRI)
data and on the corresponding functional positron emission tomography (PET) data using a quantitative approach based on the discrete
wavelet transform. Using ideas from Donoho and Johnstone,
we employed different thresholding schemes to the
wavelet transforms of the volumetric
data. The induced PET- and MRI-based warp
rankings are in agreement. However, we observe differences in warp ranking and classification sensitivity between the wavelet space
and the image
(time-domain) space analyses.