Development of Computed Tomography Algorithms

Over the past several years, computed tomography (CT) methods have advanced significantly, yielding novel analytic and iterative solutions applicable to medical CT and micro-CT. The resulting algorithms promise to improve spatial , contrast, or temporal resolution as well as to suppress artifacts and reduce radiation dose. Significant attention has been devoted to optimizing computational performance and to balancing conflicting requirements. Both theoretically oriented and application-specific issues are also being addressed. As a snapshot of the dynamically changing field of CT, this special issue includes 10 high-quality original papers. Because spiral cone-beam CT can be used for rapid vol-umetric imaging with high longitudinal resolution, the development of exact and efficient algorithms for image reconstruction from spiral cone-beam projection data has been a subject of active research in recent years. Katsevich's filtered backprojection (FBP) formula represents a significant breakthrough in this field [1]. In this special issue, Yang et al. propose a parallel implementation of Katsevich's FBP formula [2] by the one-beam cover method, in which the backprojec-tion procedure is independently driven by cone-beam projections. Based on Katsevich's work, generalized backprojec-tion filtration (BPF) and FBP algorithms are developed to reconstruct images from data collected along more flexible scanning trajectories [3]. Using these recently developed algorithms , Yu et al. propose a local region reconstruction scheme [4]. The principal idea is to deliver a normal radiation dose to a local region of interest (ROI) that may contain a lesion while applying a very low radiation dose to the structures outside the ROI. Both the FBP and BPF algorithms can produce excellent results with a minimal increment to the dose needed for purely local CT. Despite important advancements in the development of exact cone-beam reconstruction, approximate algorithms remain practically and theoretically valuable. Feldkamp et al. heuristically adapted the fan-beam FBP algorithm for approximate cone-beam reconstruction in the case of a circular scanning locus [5]. This formulation, called the FDK algorithm , is more desirable in many cases than exact cone-beam reconstruction approaches in terms of several aspects of image quality and computational implementation. Since then, many efforts have been made to extend the FDK algorithm to other scanning configurations, leading to a series of FDK-like algorithms. In this special issue, Yan et al. propose an approximate FDK-like reconstruction algorithm for tilted-gantry CT imaging [6]. The method improves the image reconstruction by filtering the projection data along a direction that is determined by CT parameters …