Decoupled automated rotational and translational registration for functional MRI time series data: The dart registration algorithm

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Abstract
A rapid, in‐plane image registration algorithm that accurately estimates and corrects for rotational and translational motion is described. This automated, one‐pass method achieves its computational efficiency by decoupling the estimation of rotation and translation, allowing the application of rapid cross‐correlation and cross‐spectrum techniques for the determination of displacement parameters. k‐space regridding and modulation techniques are used for image correction as alternatives to linear interpolation. The performance of this method was analyzed with simulations and echo‐planar image data from both phantoms and human subjects. The processing time for image registration on a Hewlett‐Packard 735/125 is 7.5 s for a 128 × 128 pixel image and 1.7 s for a 64 × 64 pixel image. Imaging phantom data demonstrate the accuracy of the method (mean rotational error, −0.09°; standard deviation = 0.17°; range, −0.44° to + 0.31°; mean translational error = −0.035 pixels; standard deviation = 0.054 pixels; range, −0.16 to + 0.06 pixels). Registered human functional imaging data demonstrate a significant reduction in motion artifacts such as linear trends in pixel time series and activation artifacts due to stimulus‐correlated motion. The advantages of this technique are its noniterative one‐pass nature, the reduction in image degradation as compared to previous methods, and the speed of computation.