A radiation imaging apparatus provided with a detector capable of improving correction accuracy at a high counting rate. The present invention is provided with: grids that remove scattered beams that emanate from an object; and a plurality of detector sub-pixels arranged so as to divide the gap between the grids into three or more segments, wherein the area of each of the detector sub-pixels located below the wall surface of the grids is larger than that of each of the other detector sub-pixels in a planar view. The size of each of the detector sub-pixels not located below the wall surface of the grids is expressed as (P.sub.gT.sub.gL.sub.split2)/N, where P.sub.g represents the pitch between the grids, T.sub.g represents the thickness of each of the grids, and N represents the number of segments formed by the detector sub-pixels between the grids.

Disclosed is a method for positioning a target in a three-dimensional CT image and a CT system for security inspection. The method includes: displaying a three-dimensional CT image; receiving a selection by a user of at least one area of the three-dimensional CT image at a viewing angle; generating at least one set of three-dimensional objects in a depth direction based on the selection; and determining a target object from the set. With the above technical solutions, the user may be facilitated in marking a suspected object in a CT image in a quick manner.

A system for imaging a target object comprises a first unmanned vehicle including a source of penetrating radiation. The first vehicle positions the source such as to direct the radiation toward the target object. A second unmanned vehicle comprises an image detector for registering a spatial distribution of the radiation as an image, in which the second vehicle positions the detector to register the distribution of radiation when transmitted through the target object. These unmanned vehicles are autonomous vehicles adapted for independent propelled motion, and comprise a positioning unit for detecting a position of the vehicle. A processing unit controls the motion of the unmanned vehicles to acquire at least two images corresponding to at least two different projection directions of the radiation through the target object. The processing unit is adapted for generating data representative of an internal structure of the target object from the at least two images.

A portable container is provided which comprises a passing room(s) allowing entry into a second area into a first area, the passing room having at least two openings with a walkway in-between. Barrier device(s) can be located in the walkway but not connected to the first or second opening. A control room(s) can also be provided, the control room being connected to the passing room(s).

System and method for screening objects of an individual, comprising an infeed station, object containers, an outfeed station, a screening station for automated screening of object containers from the infeed station and a conveyor for conveying object containers from the infeed station to the outfeed station via the screening station. The infeed station comprises an identification terminal for determining an identification of the individual, an object container dispenser for making an object container available to the individual, and a detection device for detecting the individual at the infeed station, wherein the object container dispenser is configured to make object containers available to the individual during use of the system only when said individual's identification has been determined and as long as the detection device continues to detect the presence of said individual at the infeed station.

A system for integrated cargo inspection includes a non-invasive imaging system scanning a cargo container during an offload operation to obtain a digital image of its contents, a server including a control processor to control components of the system. The components including a computer vision system to perform vision system recognition techniques on the digital image and prepare a report having image icons representing the contents, a machine learning system analytically reviewing the report to generate heuristic analysis used to train the vision system, a computing device displaying at least one of a port plan, a scan view, a results list form dialog, and a results history log graphical displays. A method to implement the system and a non-transitory computer-readable medium are also disclosed.

In a transportation security technique, images are stored that are received from image capturing equipment deployed at respective screening nodes. The images are analyzed using a machine learning model, where presence of a particular object in an image indicates that a threat condition exists at the screening node. The analyzed images are transmitted to threat assessment components in accordance with predetermined criteria. An indication that the particular object is observed in the image is received from the threat assessment components. An indication that the particular object is observed in the image is transmitted to the screening node responsive to receiving the indication that the particular object is observed in the image. An indication of whether the particular object is present at the screening node is received. The machine learning model is trained based on the received indication of whether the particular object is observed in the image.

A system identifying a source of radiation is provided. The system includes a radiation source detector and a radiation source identifier. The radiation source detector receives measurements of radiation; for one or more sources, generates a detection metric indicating whether that source is present in the measurements; and evaluates the detection metrics to detect whether a source is present in the measurements. When the presence of a source in the measurements is detected, the radiation source identifier for one or more sources, generates an identification metric indicating whether that source is present in the measurements; generates a null-hypothesis metric indicating whether no source is present in the measurements; evaluates the one or more identification metrics and the null-hypothesis metric to identify the source, if any, that is present in the measurements.

According to an embodiment, an inspection apparatus includes a communication interface and a processor. The communication interface acquires results of single-item determination, which are inspection results for individual parcels that are successively conveyed, and number-of-items information for identifying, as one parcel group, a plurality of parcels among the individual parcels. The processor identifies a plurality of parcels as one parcel group, based on the number-of-items information, determines a result of multiple-item determination, which is an inspection result for the parcel group, based on the results of the single-item determination for the individual parcels included in the parcel group, and distributes the individual parcels included in the parcel group, based on the result of the multiple-item determination.

An X-ray cargo inspection system and method. A lead-in conveyor on a first trailer receives a cargo container for inspection. An inspection module disposed on a second trailer then scans the cargo container with penetrating radiation, detects penetrating radiation that has interacted with the cargo container, and produces an inspection signal. An exit conveyor disposed on a third trailer projects the cargo container following scanning. The inspection module may contain transmission or scatter detectors, or both. Multiple lead-in conveyors may serve to load additional cargo containers for subsequent scanning by the inspection module.