  Threat Image Projection (TIP) is a technique used in X-ray security baggage
screening systems that superimposes a threat object signature onto a benign
X-ray baggage image in a plausible and realistic manner. It has been shown to
be highly effective in evaluating the ongoing performance of human operators,
improving their vigilance and performance on threat detection. However, with
the increasing use of 3D Computed Tomography (CT) in aviation security for both
hold and cabin baggage screening a significant challenge arises in extending
TIP to 3D CT volumes due to the difficulty in 3D CT volume segmentation and the
proper insertion location determination. In this paper, we present an approach
for 3D TIP in CT volumes targeting realistic and plausible threat object
insertion within 3D CT baggage images. The proposed approach consists of dual
threat (source) and baggage (target) volume segmentation, particle swarm
optimisation based insertion determination and metal artefact generation. In
addition, we propose a TIP quality score metric to evaluate the quality of
generated TIP volumes. Qualitative evaluations on real 3D CT baggage imagery
show that our approach is able to generate realistic and plausible TIP which
are indiscernible from real CT volumes and the TIP quality scores are
consistent with human evaluations.
