Rapid Automated Algorithm for Aligning and Reslicing PET... : Journal of Computer Assisted Tomography (original) (raw)
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From the Division of Nuclear Medicine and Biophysics, Department of Radiology (R.P. Woods, S. R. Cerry, and J. C. Mzziotta), and Department of Neurology (R. P. Woods and J. C. Mazziotta), University of California at Los Angeles School of Medicine, Laboratiory of Nuclear Medicine, Los Ageles, CA, U. S. A. Address correspondence and reprint requests to Dr. R. P. Woos at B2–085H Clinical Health Sciences, university of California at Los Angeles school of Medicine, 10833 LeConte Blvd., Los Angeles, CA 90024–1721, U.S.A.
Abstract
A computer algorithm for the three-dimensional (3D) alignment of PET images is described. To align two images, the algorithm calculates the ratio of one image to the other on a voxel-by-voxel basis and then iteratively moves the images relative to one another to minimize the variance of this ratio across voxels. Since the method relies on anatomic information in the images rather than on external fiducial markers, it can be applied retrospectively. Validation studies using a 3D brain phantom show that the algorithm aligns images acquired at a wide variety of positions with maximum positional errors that are usually less than the width of a voxel (1.745 mm). Simulated cortical activation sites do not interfere with alignment. Global errors in quantitation from realignment are <2%. Regional errors due to partial volume effects are largest when the gantry is rotated by large angles or when the bed is translated axially by one-half the interplane distance. To minimize such partial volume effects, the algorithm can be used prospectively, during acquisition, to reposition the scanner gantry and bed to match an earlier study. Computation requires 3–6 min on a Sun SPARCstation 2.
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