Cone-beam CT (CBCT) realizes true three-dimensional (3D) imaging in terms of its direct volume reconstruction with isotropic resolution. However, the 3D imaging performance of a CBCT system is spatially variant (or non-uniform) over the support domain, which can be quantitatively characterized by 3D point spread function (PSF). The CBCT system PSF can be experimentally measured through the use of telfon ball and edge-spread technique. For a single circular scan orbit, its volume reconstruction fails to meet data sufficiency condition, consequently causing spatial shift variance. In the pursuit of meeting data sufficiency condition, we have proposed a circle-plus-arc CB scan scheme. The overall CBCT imaging process involves several factors, including x-ray source, cone-beam projection, and computational reconstruction; each factor can in principle be characterized by a convolution kernel or PSF. In this
paper, we concentrate on the PSF characterization of circle-plus-arc algorithm. Based on the linearity of Radon transform and inverse Radon transform, we can partition the Radon domain. In particular, the circle-plus-arc scan scheme partitions the Radon domain into a donut-like region (associated with the circle scan) and funnel-like null region (provided by the arc scan). A modified FDK algorithm is responsible for donut region reconstruction, and a filtered-backprojection-styled inverse Radon transform is for the null region reconstruction. By adding them up, we obtain the complete volume reconstruction. Through the use of a bead array phantom (a 5×5×5 array), subject to cone-beam scan under different scan patterns and volume reconstruction, we calculated the local PSF blurs and the spatial variance. The result shows that, for our CBCT simulation with 28 degree cone angle, the circle scan produces a spatial variance of 9.3% and the circle-plus-arc scan reduces that to 1.8%.