Framework for optimal design of a multi-source rectangular X-ray cargo scanning system

Abstract

The first line of non-destructive inspection of cargo often relies on single or double-view X-ray radiography, which is fast but lacks depth resolution and is prone to object occlusion. In contrast, conventional X-ray computed tomography (CT) allows 3D imaging but typically relies on mechanically rotating gantries, which limits throughput and increases system complexity. Recently, multi-source fixed-gantry X-ray systems have been proposed as a promising acquisition geometry to combine high imaging speed with volumetric imaging, while reducing mechanical complexity. The precision of the reconstructed images stemming from these systems as a function of the acquisition setup has however hardly been explored. This paper proposes a flexible framework for optimal experiment design of a rectangular multi-source X-ray cargo scanning system. The proposed framework allows the experimenter to calculate the highest attainable imaging precision, as quantified by the Cramér–Rao lower bound (CRLB), as a function of the X-ray system’s geometric settings, which facilitates optimal experiment design. To illustrate this potential, several system configurations with differently positioned and oriented sources are evaluated and compared in terms of the CRLB-based A-optimality criterion.