TRANSMISSION MAXIMUM-LIKELIHOOD RECONSTRUCTION WITH ORDERED SUBSETS FOR CONE-BEAM CT

An iterative algorithm is presented for accelerated reconstruction of cone beam transmission CT data (CBCT). CBCT supplies an attenuation map for SPECT attenuation compensation and anatomical correlation. Iterative algorithms are necessary to reduce truncation artifacts and 3D reconstruction artifacts. An existing transmission maximum-likelihood algorithm (TRML) is accurate but the reconstruction time is too long. The new algorithm is a modified EM algorithm, based on ordered subsets (OSEM). OSEM was evaluated in comparison to TRML using a thorax phantom and a 3D Defrise phantom. A wide range of image measures were evaluated, including spatial resolution, noise, log likelihood, region quantification, truncation artifact removal, and 3D artifact removal. For appropriate subset size, OSEM produced essentially the same image as TRML, but required only one-tenth as many iterations. Thus, adequate images were available in two to four iterations (20-30 min on a SPARC 2 workstation). Further, OSEM still approximately maximizes likelihood: divergence occurs only for very high (and clinically irrelevant) iterations. Ordered subsets are likely to be useful in other geometries (fan and parallel) and for emission CT as well. Therefore, with ordered subsets, high-quality iterative reconstruction is now available in clinically practical reconstructions times.