Explosive Detection in Aviation Applications Using CT

Abstract

CT scanners are deployed world-wide to detect explosives in checked and carry-on baggage. Though very similar to single- and dual-energy multi-slice CT scanners used today in medical imaging, some recently developed explosives detection scanners employ multiple sources and detector arrays to eliminate mechanical rotation of a gantry, photon counting detectors for spectral imaging, and limited number of views to reduce cost. For each bag scanned, the resulting reconstructed images are first processed by automated threat recognition algorithms to screen for explosives and other threats. Human operators review the images only when these automated algorithms report the presence of possible threats. The US Department of Homeland Security (DHS) has requirements for future scanners that include dealing with a larger number of threats, higher probability of detection, lower false alarm rates and lower operating costs. One tactic that DHS is pursuing to achieve these requirements is to augment the capabilities of the established security vendors with third-party algorithm developers. A third-party in this context refers to academics and companies other than the established vendors. DHS is particularly interested in exploring the model that has been used very successfully by the medical imaging industry, in which university researchers develop algorithms that are eventually deployed in commercial medical imaging equipment. The purpose of this paper is to discuss opportunities for third-parties to develop advanced reconstruction and threat detection algorithms.