Variance-based iterative image reconstruction from few views in limited-angle C-arm computed tomography

C-arm cone-beam computed tomography offers CT-like 3D imaging capabilities, but with the additional advantage of being appropriate for interventional suites. Due to the limitations of the data acquisition system, projections are oft acquired in a short scan angular range, resulting in significant artifacts, if conventional analytic formulas are applied. Furthermore, the presence of high-density objects, like metal parts, induces streak-like artifacts, which can obscure relevant anatomy. We present a new algorithm to reduce such artifacts and enhance the quality of reconstructed 3D volume. We make use of the variance of estimated voxel values over all projections to decrease the ground artifact level. The proposed algorithm is less sensitive to data truncation, and does not require explicit estimation of missing data. The number of required images is very low (up to 56 projections), which have several benefits, like significant reduction of patient dose and shortening of the acquisition time. The performance of the proposed method is demonstrated based on simulations and phantom data.