Improved quality of re-sliced MR images using re-normalized sinc interpolation

This article shows that re-normalizing the interpolation kernel for a const ant integral can make a significant improvement in performance of sine inte rpolation methods. A comparison was performed between standard and re-norma lized sine kernels of various sizes using data from four commonly used magn etic resonance (MR) imaging sequences. Standard rotations were performed an d compared with a "gold standard" data set generated by use of a large (13 x 13 x 13) sine kernel. Measurements of systematic pixel intensity offset e rror and variance of generated residuals were used to estimate resultant in terpolation error, Theoretical estimates of the consequent savings in compu tation time were compared with the measured time required for each algorith m and with the automated image registration (AIR) program. The use of a sma ll (5 x 5 x 5) re-normalized kernel produced relative errors comparable to those in the gold standard data set, allowing saving in computation time of up to 30 times in comparison with standard sine interpolation. This approa ch brings the implementation of MR volume re-slicing much closer to the dem ands of a clinical environment. (C) 1999 Wiley-Liss, Inc.