A new rebinning algorithm for 3D PET data

3D acquisition mode in PET is a way to increase the sensitivity of the scanner. To reconstruct the 3D data it is necessary to use either a fully 3D reconstruction algorithm or, alternatively, a rebinning algorithm followed by 2D reconstruction. The advantages of the 2^nd approach are higher speed and reduced data size. Rebinning algorithms may become more important in the future with time-of-flight PET due to the increased dimensionality of the projection data. Although two exact rebinning algorithms have been developed, the most commonly used method today is the approximate Fourier rebinning algorithm. These three methods are based on analytic solutions in the frequency domain and involve geometric approximations, which may be significant for some scanner geometries. They also require attenuation corrected data, which can lead to complications since some reconstruction algorithms work better with non-attenuation corrected data. We have developed a novel rebinning algorithm, called reprojection rebinning (RP-RB), which is free from theoretical and geometric approximations as well as from the requirement of attenuation correction. It is based on an initial reconstruction of a 2D data-subset, which results in a somewhat sub-optimal utilization of the oblique data. The results can be improved, however, by an iterative procedure. We have tested RP-RB using simulated phantom data, showing an SD reduction in the central transaxial plane after the 1^st, 2^nd and 3^rd iteration by a factor of 3.0, 3.5 and 4.1, respectively, as compared to 2D data only. There was also a very good spatial accuracy in images reconstructed from noiseless data, even for scanner geometries with large acceptance angles.