Quantitative analysis of the efficacy of gradient table correction on improving the accuracy of fiber tractography
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Updated: May 9, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Ali Ersoz1, Volkan Emre Arpinar, Sean Dreyer
1Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Purpose:
Several groups suggested that the gradient table of a DTI data set should be reoriented to compensate for head motion. Although the effects of this correction were demonstrated qualitatively, its efficacy was not demonstrated quantitatively to date. The main goal of this study was to investigate the efficacy of gradient table correction on improving the accuracy of fiber tractography.
Methods:
First, the effects of gradient table correction on the estimation of fractional anisotropy (FA) maps and the primary diffusion direction were quantified and compared with the inherent uncertainty in the estimation process. Then, the effects of gradient table correction on tractography were quantified.
Results:
The corrections in FA values were only a fraction of the typical values seen in major fasciculi and inter-subject variance. The corrections to the primary diffusion direction were also much smaller than the uncertainty inherent in the estimation of its direction. However, the directional estimates were biased due to head motion and deviated fiber tracking.
Conclusions:
Corrections to FA values were negligible and are not expected to affect group comparisons. However, a small but consistent bias was introduced to the estimates of primary diffusion direction, which might affect brain connectivity analyses based on fiber tracking.
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