Bias in Diffusion Tensor-Derived
Quantities Depend on the Number of DWIs Composing the DT-MRI Dataset
Firouzeh Tannazi1, Lindsay Walker1,
Michael Curry1, Carlo Pierpaoli1
1STBB/PPITS/NICHD/NIH, Bethesda, MD, United
States
In this study we investigate the effects of the number
of images comprising the DTI data set on the statistical properties of
diffusion tensor eigenvalues and anisotropy indices derived from them. The
results of Monte Carlo simulations along with the analysis of phantom DTI
data indicate an overall underestimation of Eig3 and an overestimation of FA
and Eig1 as the number of images in DTI estimation is reduced.
