Abstract: One or more systems and/or techniques are provided to identify objects comprised in a compound object without segmenting three-dimensional image data of the potential compound object. Two-dimensional projections of a potential compound object (e.g., Eigen projections) are examined to identify the presence of known objects. The projections are compared to signatures, such as morphological characteristics, of one or more known objects. If it is determined based upon the comparison that there is a high likelihood that the compound object comprises a known object, a portion of the projection is masked, and it is compared again to the signature to determine if this likelihood has increased. If it has, a sub-object of the compound object may be classified based upon characteristics of the known object (e.g., the compound object may be classified as a potential threat item if the known object is a threat item).

Abstract: Representations of an object in an image generated by an imaging apparatus can comprise two or more separate sub-objects, producing a compound object. Compound objects can negatively affect the quality of object visualization and threat identification performance. As provided herein, a compound object can be separated into sub-objects. Topology score map data, representing topological differences in the potential compound object, may be computed and used in a statistical distribution to identify modes that may be indicative of the sub-objects. The identified modes may be assigned a label and a voxel of the image data indicative of the potential compound object may be relabeled based on the label assigned to a mode that represents data corresponding to properties of a portion of the object that the voxel represents to create image data indicative of one or more sub-objects.

Abstract: Representations of an object (110) in an image generated by an imaging apparatus (100) can comprise two or more separate sub-objects, producing a compound object (500). Compound objects can negatively affect the quality of object visualization and threat identification performance. As provided herein, a compound object (500) can be separated into sub-objects. Three-dimensional image data of a potential compound object (500) is projected into a two-dimensional manifold projection (504), and segmentation is performed on the two-dimensional manifold projection of the compound object to identify sub-objects. Once sub-objects are identified, the two-dimensional, segmented manifold projection (900) is projected into three-dimensional space (1104). A three-dimensional segmentation may then be performed to identify additional sub-objects of the compound object that were not identified by the two-dimensional segmentation.

Abstract: A method of and a system for displaying volumetric data on a 2D or 3D display are provided. In particular, a method of highlighting objects using contours of selected objects on a 2D display and on a 3D stereoscopic display is provided. The contour highlighting method provides users an attention cue of highlighted objects while preserves the details of objects to be observed. The applications of the 3D display workstation for security luggage screening and for medical diagnosis and surgical planning are also provided.

Abstract: A CT scanning system may include a multi-pixel x-ray source, and a detector array. The multi-pixel x-ray source may have a plurality of pixels that are disposed along a z-axis, and that are sequentially activated so as to controllably emit x-rays in response to incident electrons. The detector array may have one or more rows of x-ray detectors that detect the x-rays that are emitted from the pixels and have traversed an object, and generate data for CT image reconstruction system. In third generation CT scanning systems, the number of detector rows may be reduced. Multi-pixel x-ray source implementation of saddle curve geometry may render a single rotation single organ scan feasible. Using a multi-pixel x-ray source in stationary CT scanning systems may allow x-ray beam design with a minimal coverage to satisfy mathematical requirements for reconstruction.

Abstract: A method of and a system for automatic object display of volumetric CT data for fast on-screen threat resolution are disclosed, wherein the CT data includes a CT image in a single energy CT scanner, or a CT image and a Z image in a multi-energy CT scanner, and a label image defining each object as a plurality of voxels of the volumetric CT data. The method comprises generating volumetric CT image data corresponding to a scanned bag; performing automatic threat detection to generate a label image; processing the volumetric CT data and the label image to obtain visualization parameters for each object; automatically generating display images for each object using corresponding visualization parameters; and displaying the generated display images for on-screen threat resolution.

Abstract: Potential threat items may be concealed inside objects, such as portable electronic devices, that are subject to imaging for example, at a security checkpoint. Data from an imaged object can be compared to pre-determined object data to determine a class for the imaged object. Further, an object can be identified inside a container (e.g., a laptop inside luggage). One-dimensional Eigen projections can be used to partition the imaged object into partitions, and feature vectors from the partitions and the object image data can be used to generate layout feature vectors. One or more layout feature vectors can be compared to training data for threat versus non-threat-containing items from the imaged object's class to determine if the imaged object contains a potential threat item.

Abstract: Radiation flux can be adjusted “on the fly” as an object (204) is being scanned in a security examination apparatus. Adjustments are made to the radiation flux based upon radiation incident on a first radiation detector (226) in an upstream portion (233) of an examination region. The object under examination is thus exposed to different radiation flux in coordination with a downstream motion (235) of the object relative to a second radiation detector (228). The radiation flux is adjusted so that a sufficient number of x-rays (that traverse the object) are incident on the second radiation detector. Images of the object can then be generated based upon data from the second radiation detector, where these images are thus of a desired/higher quality.

Abstract: The disclosed CT scanner comprises at least one source of X-rays; a detector array comprising a plurality of detectors; and an X-ray filter mask arrangement disposed between the source of X-rays and detector array so as to modify the spectra of the X-rays transmitted from the source through the mask to at least some of the detectors so that the X-ray spectra detected by at least one set of detectors is different from the X-ray spectra detected by at least one other set of detectors.

Abstract: A method of and a system for identifying objects using local distribution features from multi-energy CT images are provided. The multi-energy CT images include a CT image, which approximates density measurements of scanned objects, and a Z image, which approximates effective atomic number measurements of scanned objects. The local distribution features are first and second order statistics of the local distributions of the density and atomic number measurements of different portions of a segmented object. The local distributions are the magnitude images of the first order derivative of the CT image and the Z image. Each segmented object is also divided into different portions to provide geometrical information for discrimination.

Abstract: The disclosed CT scanner comprises at least one source of X-rays; a detector array comprising a plurality of detectors; and an X-ray filter mask arrangement disposed between the source of X-rays and detector array so as to modify the spectra of the X-rays transmitted from the source through the mask to at least some of the detectors so that the X-ray spectra detected by at least one set of detectors is different from the X-ray spectra detected by at least one other set of detectors.

Abstract: A method of and a system for variable pitch CT scanning for baggage screening and variable pitch image reconstruction are disclosed.

Abstract: A method of and a system for displaying volumetric multi-energy CT images are disclosed, wherein a CT image, a Z image, and a label image from an automatic explosive detection are provided, are disclosed. The method comprises generating an index image through a nonlinear transformation of the CT image, the Z image, and the label image, rotating and coloring the index image as desired, and rendering and displaying the rotated and colored image.

Abstract: A method of and a system for splitting a compound object using multi-energy CT data including a density and an atomic number measurements are provided. The method comprises: compound object detection; computing a two-dimensional DZ distribution of a compound object; identifying clusters within the DZ distribution; assigning a component label to each object voxel based on the DZ distribution clusters; and post-processing the set of voxels identified as belonging to each component.

Abstract: A method of and a system for identifying objects using histogram segment features from multi-energy CT images are provided. The multi-energy CT images include a CT image, which approximates density measurements of scanned objects, and a Z image, which approximates effective atomic number measurements of scanned objects. The method comprises: computing a density histogram for each potential threat object; smoothing the density histogram using a low-pass filter; identifying peaks in the smoothed density histogram; assigning a segment to each peak; computing histogram segment features for each segment; classifying each potential threat object into a threat or a non-threat using computed features.

Abstract: A method of and a system for variable pitch CT scanning for baggage screening and variable pitch image reconstruction are disclosed.

Abstract: A method of and a system for destreaking the photoelectric image in multi-energy computed tomography are provided, wherein the photoelectric projections are generated from the projection data acquired using at least two x-ray spectra for scanned objects; wherein a neighboring scheme is provided; the method comprises computing the statistics including mean and standard deviation using the neighboring scheme; calculating an upper limit and a lower limit from the computed statistics; detecting outliers in the photoelectric projections using the upper and lower limits; and replacing values of outliers using the upper or lower limit.

Abstract: A method of and a system for automatic object display of volumetric CT data for fast on-screen threat resolution are disclosed, wherein the CT data includes a CT image in a single energy CT scanner, or a CT image and a Z image in a multi-energy CT scanner, and a label image defining each object as a plurality of voxels of the volumetric CT data. The method comprises generating volumetric CT image data corresponding to a scanned bag; performing automatic threat detection to generate a label image; processing the volumetric CT data and the label image to obtain visualization parameters for each object; automatically generating display images for each object using corresponding visualization parameters; and displaying the generated display images for on-screen threat resolution.

Abstract: A method of and a system for detecting anomalies in projection images generated by CT scanners are provided. One type of anomaly of particular interest is bright or/and dark dots in projection images, which correspond to streak artifacts in the CT images. The method for detecting such bright or/and dark dots in projection images comprises: generating projection images; computing a CFAR distance map; computing a preliminary dot map; generating dot histograms; and detecting bright dots or/and dark dots based on the generated histograms.

Abstract: A method of and a system for extracting 3D bag images from continuously reconstructed 2D image slices are provided. The method detects the boundaries of baggage in the reconstructed images, and provides better flexibilities for threat detection and displaying. The method comprises detecting starting and ending slices using multiple slices, counting bag slices, splitting 3D bag images when maximum number of slices of a 3D bag image is reached, and creating overlapping slices for the split 3D bag images.