An optimal rotator for iterative reconstruction

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Abstract
For implementations of iterative reconstruction algorithms that rotate the image matrix, the characteristics of the rotator may affect the reconstruction quality. Desirable qualities for the rotator include: 1) preservation of global and local image counts; 2) accurate count positioning; 3) a uniform and predictable amount of blurring due to the rotation. A new rotation method for iterative reconstruction is proposed which employs. Gaussian interpolation. This method was compared to standard rotation techniques and is shown to be superior to standard techniques when measured by these qualities. The computational cost was demonstrated to be only slightly more than bilinear interpolation.