Quantitative assessment of mis-registration issues of diffusion tensor imaging (DTI)
2012
Image distortions caused by eddy current and patient motion have been two major sources of the mis-registration issues
in diffusion tensor imaging (DTI). Numerous registration methods have been proposed to correct them. However, quality
control of DTI remains an important issue, because we rarely report how much mis-registration existed and how well
they were corrected. In this paper, we propose a method for quantitative reporting of DTI data quality. This registration
method minimizes a cost function based on mean square tensor fitting errors. Registration with twelve-parameter full
affine transformation is used. From the registration result, distortion and motion parameters are estimated. Because the
translation parameters involve both eddy-current-induced image translation and the patient motion, by analyzing the
transformation model, we separate them by removing the contributions that are linearly correlated with diffusion
gradients. We define the metrics measuring the amounts of distortion, rotation, translation. We tested our method on a
database with 64 subjects and found the statistics of each of metrics. Finally we demonstrate that how these statistics can
be used for assessing the data quality quantitatively in several examples.
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