Evolution of computer technology for fast cone beam backprojection

Cone-beam reconstruction (CBR) is useful for producing volume images from projections in many fields including medicine, biomedical research, baggage scanning, paleontology, and nondestructive manufacturing inspection. CBR converts a set of two-dimensional (2-D) projections into a three-dimensional (3-D) image of the projected object. The most common algorithm used for CBR is referred to as the Feldkamp-Davis-Kress (FDK) algorithm; this involves filtering and cone-beam backprojection steps for each projection of the set. Over the past decade we have observed or studied FDK on platforms based on many different processor types, both single-processor and parallel-multiprocessor architectures. In this paper we review the different platforms, in terms of design considerations that include speed, scalability, ease of programming, and cost. In the past few years, the availability of programmable special processors (i.e. graphical processing units [GPUs] and Cell Broadband Engine [BE]), has resulted in platforms that meet all the desirable considerations simultaneously.