Abstract: An example method includes capturing, via an x-ray machine, a plurality of x-ray images of a patient covering a number of different anatomy of the patient in any order, using a machine learning algorithm to process the plurality of x-ray images for identification of an anatomy in respective x-ray images of the plurality of x-ray images, associating a label with each of the plurality of x-ray images based on the identification of the anatomy, positioning each of the plurality of x-ray images upright based on a preset coordinate scheme for the anatomy, arranging the plurality of x-ray images into a predetermined order based on the species of the patient, and generating and outputting a data file including the plurality of x-ray images in the predetermined order, positioned upright, and labeled.

Abstract: A modular imaging system includes an antenna panels, a sensor, and at least one data processor. The antenna panels include an array of antenna elements including at least two antenna elements separated by a spacing more than a half wavelength. The plurality of antenna panels are configurable to be spatially arranged and oriented with respect to one another to measure radar returns of an observation domain for a target. The sensor has a field of view overlapping the observation domain and for measuring an image. The at least one data processor forms part of at least one computing system and is adapted to receive data characterizing the optical image and the radar returns, determine a spatial location of the target, and construct a radar return image of the target using a sparsity constraint determined from the spatial location of the target. Related apparatus, systems, techniques, and articles are also described.

Abstract: A modular imaging system includes an antenna panels, a sensor, and at least one data processor. The antenna panels include an array of antenna elements including at least two antenna elements separated by a spacing more than a half wavelength. The plurality of antenna panels are configurable to be spatially arranged and oriented with respect to one another to measure radar returns of an observation domain for a target. The sensor has a field of view overlapping the observation domain and for measuring an image. The at least one data processor forms part of at least one computing system and is adapted to receive data characterizing the optical image and the radar returns, determine a spatial location of the target, and construct a radar return image of the target using a sparsity constraint determined from the spatial location of the target. Related apparatus, systems, techniques, and articles are also described.

Abstract: Embodiments of an Array CT scanning system for x-ray scanning objects (e.g., scanning airline baggage, packages, and cargo) can include a conveyor configured to transport baggage through a tunnel, a bottom mounted x-ray source configured to provide five fan beams through the tunnel, a side mounted x-ray source disposed at a height higher than the conveyor and configured to provide a fan beam through the tunnel, and a plurality of detectors disposed across the arcs of each of the fan beams. An image processing system can be configured to provide 3D type images of a scanned bag as a function of the information received from the detectors. The images can be derived through interpolation of the scan data. An operator can manipulate the image data and partially rotate the bag to discern objects located within. A side tray is provided to allow an operator to remove a suspect bag from an operational flow of bags. Image information can be stored for subsequent review.