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Jeff J. Orchard, M. Stella Atkins School of Computing Science, Simon Fraser University The AIR package performs registration using only tri-linear interpolation (1). As a result, its registration accuracy suffers (2). Use AIR’s registration algorithm iteratively as a means to generate adjustments, but perform intermediate resampling steps with more accurate interpolation programs included in the AIR package. Input: base volume and float volume resamp volume = float volume best guess = identity transformation for i=1 to 4 do resamp volume use reslice to apply the best guess to the floating volume adjustment use alignlinear between the base and resamp volume best guess use combine_air to incorporate adjustment into the best guess next i report the best guess Pseudocode The motion plots below compare the estimates of AIR and iAIR to the true motion. The iAIR algorithm performed 4 iterations, resampling using the scanline chirp-z interpolation method. Iterated AIR AlgorithmResults ProblemSolution The graph on the right shows the mean brain voxel displacement from its true position after correction using AIR and iAIR motion estimates. The iAIR algorithm exhibits a significantly smaller mean displacement for most volumes. The iAIR algorithm was tested on a simulated fMRI dataset created by adding motion and Gaussian noise (2.5%) to 40 copies of an original EPI volume with dimensions 64x64x30. The rigid-body transformations were applied to the volumes using Fourier methods (3), supersampled by a factor of 2 in each dimension. References 1. Woods RP, Grafton ST, Holmes CJ,Cherry SR, Mazziotta JC. Automated image registration: I. General methods and intrasubject, intramodality validation. J Comput Assist Tomogr 1998;22:141-154. 2. Hajnal JV, Saeed N, Soar EJ, Oatridge A, Young IR, Bydder GM. A registration & interpolation procedure for subvoxel matching of serially acquired MR images. J Comput Assist Tomogr 1995;19(2):289-296. 3. Cox RW, Jesmanowicz A. Real-time 3D image registration for functional MRI. Magn Reson Med 1999;42:1014-1018. This technique uses AIR’s registration program ( alignlinear ) as an incremental motion estimator. The sinc resampling ( reslice ) between iterations of iAIR is more robust than tri-linear interpolation, adding accuracy to the intermediate motion correction steps. If sinc interpolation was added to AIR’s registration program, the same accuracy could be achieved. However, in its absence, iteration and careful resampling techniques can still achieve comparable accuracy. Conclusions This method, which we call “Iterated AIR”, or iAIR, uses 3 programs included in the AIR 3.08 distribution package: reslice, combine_air, and alignlinear. The algorithm iteratively adjusts a cumulative “best guess” transformation. For each iteration, the iAIR algorithm calls reslice to obtain a transformed version of the floating volume, using sinc interpolation. Then, alignlinear is used to estimate the transformation between the newly resampled volume and the base volume. This estimate is then used to adjust the current best guess using the program combine_air. We want to find the transformation that optimally aligns a “floating” volume with a “base” volume using the Automated Image Registration (AIR) package. Goal Resamp. volume combine_air Combine two transformations using matrix multiplication. adjustment new best guess Transformation best guess reslice Apply the best guess transformation to the floating volume, producing a resampled volume. alignlinear Determine the best transformation to align the two volumes using tri-linear interpolation. BaseResamp Transformation adjustment Floating volume Resamp. volume START with the identity transform best guess Acknowledgments The authors thank Dr. Bruce Bjornson of the British Columbia’s Children’s Hospital for helpful discussions. Also, this work was supported in part by the Natural Sciences and Engineering Research Council of Canada. Volume Number 030401020 Displacement (mm) iAIR AIR Key: mm Degrees Pitch Yaw Roll Left Posterior Superior Volume Number 010203040 iAIR AIR True Key:
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