Interlaced interpolation weighting functions for multislice helical computed tomography

Abstract

We develop a new projection weighting function for interpolation and reconstruction of multislice helical computed tomography (CT) data with the hope of improving longitudinal resolution and reducing longitudinal aliasing in reconstructed volumes. The weighting function is based on the application of the Papoulis generalized sampling theorem to the interlaced longitudinal samples acquired by the multislice scanner. We call the approach 180MII, for multislice interlaced interpolation. For pitch 3, the 180MII approach yields high-quality images of the 3-D Shepp-Logan phantom as well as a longitudinal modulation transfer function (MTF) superior to that of the widely used 180MLI approach, which is based on the use of linear interpolation. The approach also suppresses the aliasing component expected from analysis of the longitudinal sampling pattern that arises when one neglects the small cone angle present in multislice helical CT. The approach is not as successful at mitigating an additional unexpected aliasing component that can be attributed to this cone angle. The presence of this conebeam effect is interesting and significant in its own right since it reveals the limitations of any multislice helical CT algorithm that ignores the cone angle.