Evaluation of spectral CT data acquisition methods via non-stochastic variance maps

Abstract

Recently, photon counting detectors capable of extracting spectral information have received much attention in CT, with promise of using spectral information to construct material basis images, correct beam-hardening artifacts, or provide improved imaging of K-edge contrast agents. 1, 2 In this work, we focus on the goal of constructing images of basis material maps, and investigate the feasibility of analytically computing pixel variance maps for these images, so that alternative data acquisition and reconstruction methods can be compared and evaluated with respect to their noise properties. Our approach is based on linearization of the basis material decomposition and reconstruction operations, and we therefore demonstrate the method using the ubiquitous filtered back-projection algorithm, which is linear. We then performed preliminary investigation of the method by comparing basis material variance maps for two data acquisition methods that were previously found to have different noise properties: 3 two-sided bin measurements acquired from separate, independent data realizations and two-sided bin measurements acquired from a single data realization.