Ultra high-speed transaxial image reconstruction of the heart, lungs, and circulation via numerical approximation methods and optimized processor architecture

Abstract

A high temporal resolution scanning multiaxial tomography unit, the Dynamic Spatial Reconstructor (DSR), presently under development will be capable of recording multiangular X-ray projection data of sufficient axial range to reconstruct a cylindrical volume consisting of up to 240 contiguous 1-mm thick cross sections encompassing the intact thorax. At repetition rates of up to 60 sets of cross sections per second, the DSR will thus record projection data sufficient to reconstruct as many as 14 400 cross-sectional images during each second of operation. Use of this system in a clinical setting will be dependent upon the development of software and hardware techniques for carrying out X-ray reconstructions at the rate of hundreds of cross sections per second. A conceptual design, with several variations, is proposed for a special purpose hardware reconstruction processor capable of completing a single cross section reconstruction within 1 to 2 msec. In addition, it is suggested that the amount of computation required to execute the filtered back-projection algorithm may be decreased significantly by the utilization of approximation equations, formulated as recursions, for the generation of internal constants required by the algorithm. The effects on reconstructed image quality of several different approximation methods are investigated by reconstruction of density projections generated from a mathematically simulated model of the human thorax, assuming the same source-detector geometry and X-ray flux density as will be employed by the DSR. These studies have indicated that the prudent application of numerical approximations for the generation of internal constants will not cause significant degradation in reconstructed image quality and will in fact require substantially less auxiliary memory and computational capacity than required by direct execution of mathematically exact formulations of the reconstruction algorithm.