Determination of calibration parameters of a VRX CT system using an "Amoeba" algorithm

Abstract

Efforts to improve the spatial resolution of CT scanners have focused mainly on reducing the source and detector element sizes, ignoring losses from the size of the secondary-ionization charge "clouds" created by the detected x-ray photons, i.e., the "physics limit." This paper focuses on implementing a technique called "projective compression," which allows further reduction in effective cell size while overcoming the physics limit as well. Projective compression signifies detector geometries in which the apparent cell size is smaller than the physical cell size, allowing large resolution boosts. A realization of this technique has been developed with a dual-arm "variable-resolution x-ray" (VRX) detector. Accurate values of the geometrical parameters are needed to convert VRX outputs to formats ready for optimal image reconstruction by standard CT techniques. The required calibrating data are obtained by scanning a rotating pin and fitting a theoretical parametric curve (using a multi-parameter minimization algorithm) to the resulting pin sinogram. Excellent fits are obtained for both detector-arm sections with an average (maximum) fit deviation of ∼0.05 (0.1) detector cell width. Fit convergence and sensitivity to starting conditions are considered. Pre- and post-optimization reconstructions of the alignment pin and a biological subject reconstruction after calibration are shown.