Parallel Implementation of a X-Ray Tomography Reconstruction Algorithm for High-Resolution Studies

Abstract

Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flatpanel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp, Davis and Kress (FDK). Currently there is a strong need to speed-up the reconstruction of CT data in order to extend its clinical applications. The evolution of the semiconductor detector panels has resulted in an increase of detector elements density, which produces a higher amount of data to process. This work focuses on both standard and future high-resolution studies, in which multiple level of parallelism will be needed in the reconstruction process. In addition, this paper addresses the future challenges of processing high-resolution images in many-core and distributed architectures.