We review the relatively immature field of automated image analysis for X-ray\ncargo imagery. There is increasing demand for automated analysis methods that\ncan assist in the inspection and selection of containers, due to the\never-growing volumes of traded cargo and the increasing concerns that customs-\nand security-related threats are being smuggled across borders by organised\ncrime and terrorist networks. We split the field into the classical pipeline of\nimage preprocessing and image understanding. Preprocessing includes: image\nmanipulation; quality improvement; Threat Image Projection (TIP); and material\ndiscrimination and segmentation. Image understanding includes: Automated Threat\nDetection (ATD); and Automated Contents Verification (ACV). We identify several\ngaps in the literature that need to be addressed and propose ideas for future\nresearch. Where the current literature is sparse we borrow from the\nsingle-view, multi-view, and CT X-ray baggage domains, which have some\ncharacteristics in common with X-ray cargo.\n