Analogic Corporation

Other

Zhengrong Ying

Sergey Simanovsky

Ram Naidu

Carl R Crawford

Matthew Waggener Hirsch

Julia Pavlovich

Chitra Subramanian

Baoming Hong

David A Schafer

Sorin Marcovici

Kyle Guilbert

Douglas Q Abraham

Basak Ulker Karbeyaz

Aleksander Roshi

Anton M Deykoon

Govindarajan T Srinivasan

Gregory L Larson

Anuradha Aiyer

Nima Shokrollahi

Dong-Yueh Liang

Purvin Desai

A system for iteratively reconstructing computed tomography images through three domains is disclosed. The system comprises a raw domain processor, a projection domain processor, and an image domain processor. The system also comprises two iterative loops: one is through a raw synthesizer connecting the raw domain processor and the projection domain processor, and the other is through a projection synthesizer connecting the projection domain processor and the image domain processor respectively.

System for iteratively reconstructing computed tomography images through three domains

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. Three-dimensional image data of a potential compound object is projected into a two-dimensional manifold projection, 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 is projected into three-dimensional space. 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.

Compound object separation

An apparatus for detecting X-rays and converting the detected X-ray intensities into digital signals is disclosed. The apparatus places Analog to Digital Conversion (ADC) chips directly under a scintillator array along the X-ray beam direction and uses a shield that is placed between a photodiode substrate and an Analog to Digital Conversion (ADC) chip to block X-rays from directly reaching the dies of the ADC chips, which are sensitive to X-rays. Also an X-ray CT system utilizing the disclosed apparatus for detecting X-rays is provided.

Apparatus for detecting X-rays

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.

CT scanning systems and methods using multi-pixel x-ray sources

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. Three-dimensional image data of a potential compound object () is projected into a two-dimensional manifold projection (), 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 () is projected into three-dimensional space (). 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.

An Adjustable Photon Detection System (APDS) for multi-slice X-ray CT systems and a multi-slice X-ray CT system using the APDS are disclosed; wherein the APDS can be adjusted to be aligned to different X-ray source positions; wherein the multi-slice X-ray CT system comprises one or more X-ray sources, and one or more APDS; wherein the multi-slice X-ray CT system may also include a detector position calculator for calculating effective detector positions and a detector position corrector for correcting projection data using calculated effective detector positions.

Adjustable photon detection systems for multi-slice X-ray computed tomography systems

Radiation flux can be adjusted 'on the fly' as an object () is being scanned in a security examination apparatus. Adjustments are made to the radiation flux based upon radiation incident on a first radiation detector () in an upstream portion () of an examination region. The object under examination is thus exposed to different radiation flux in coordination with a downstream motion () of the object relative to a second radiation detector (). 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.

Radiation modulation in a security examination apparatus

A Data Measurement and Acquisition System (DMAS) for multi-slice X-ray CT systems and multi-slice X-ray CT systems using the DMAS are disclosed; wherein the DMAS comprises a plurality of X-ray scintillators, a plurality of photodiode modules, a plurality of digitizing cards, one or more motherboards, and an arced support structure for mounting and securing the photodiode modules, the digitizing cards, and the motherboard(s); wherein the multi-slice X-ray CT systems comprises one or more X-ray sources, and one or more DMAS.

Configurable data measurement and acquisition systems for multi-slice X-ray computed tomography systems

A detector system for multi-slice X-ray Computed Tomography (CT) system is disclosed. The detector system comprises a plurality of X-ray detector modules for detecting X-ray photons; wherein each detector module is divided into individual detector elements organized in a matrix fashion with element rows (z-axis for row direction) and element columns (x-axis for column direction) for detecting X-ray photons; wherein the individual detector elements are interspaced by gaps (areas that do not detect radiation), which are also organized in a matrix fashion with gap rows and gap columns; and an anti-scatter collimator comprising a plurality of anti-scatter plates, which is placed above the detector modules and aligned to focus on an X-ray source of the CT system; wherein some or all of the anti-scatter plates are placed above the detector elements; wherein those anti-scatter plates that are placed above the detector elements block a portion of primary X-ray photons from the X-ray source in addition to scattered X-ray photons from reaching the detector elements.

Anti-scatter collimators for detector systems of multi-slice X-ray computed tomography systems

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).

Object classification using two-dimensional projection

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.

Detecting concealed threats

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.

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.

Method of and system for automatic object display of volumetric computed tomography images for fast on-screen threat resolution

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.

Growing community of inventors

Wakefield, MA, United States of America

Zhengrong Ying