Stationary tomographic X-ray imaging systems for automatically sorting objects based on generated tomographic images

Abstract
An X-ray imaging inspection system for inspecting items comprises an X-ray source 10 extending around an imaging volume 16, and defining a plurality of source points 14 from which X-rays can be directed through the imaging volume. An X-ray detector array 12 also extends around the imaging volume 16 and is arranged to detect X-rays from the source points which have passed through the imaging volume, and to produce output signals dependent on the detected X-rays. A conveyor 20 is arranged to convey the items through the imaging volume 16.
Description
FIELD

The present application relates to X-ray scanning and, in particular, in systems for enabling the security screening of baggage, packages and other suspicious objects.


BACKGROUND

X-ray computed tomography (CT) scanners have been used in security screening in airports for several years. A conventional system comprises an X-ray tube that is rotated about an axis with an arcuate X-ray detector also rotated at the same speed around the same axis. The conveyor belt on which the baggage is carried is placed within a suitable aperture around the central axis of rotation, and moved along the axis as the tube is rotated. A fan-beam of X-radiation passes from the source through the object to be inspected to the X-ray detector array.


The X-ray detector array records the intensity of X-rays passed through the object to be inspected at several locations along its length. One set of projection data is recorded at each of a number of source angles. From these recorded X-ray intensities, it is possible to form a tomographic (cross-sectional) image, typically by means of a filtered back projection algorithm. In order to produce an accurate tomographic image of an object, such as a bag or package, it can be shown that there is a requirement that the X-ray source pass through every plane through the object. In the arrangement described above, this is achieved by the rotational scanning of the X-ray source, and the longitudinal motion of the conveyor on which the object is carried.


In this type of system the rate at which X-ray tomographic scans can be collected is dependent on the speed of rotation of the gantry that holds the X-ray source and detector array. In a modern CT gantry, the entire tube-detector assembly and gantry will complete two to four revolutions per second. This allows up to four or eight tomographic scans to be collected per second respectively.


As the state-of-the-art has developed, the single ring of X-ray detectors has been replaced by multiple rings of detectors. This allows many slices (typically 8) to be scanned simultaneously and reconstructed using filtered back projection methods adapted from the single scan machines. With a continuous movement of the conveyor through the imaging system, the source describes a helical scanning motion about the object. This allows a more sophisticated cone-beam image reconstruction method to be applied that can in principle offer a more accurate volume image reconstruction.


In a further development, swept electron beam scanners have been demonstrated in medical applications whereby the mechanical scanning motion of the X-ray source and detectors is eliminated, being replaced by a continuous ring (or rings) of X-ray detectors that surround the object under inspection with a moving X-ray source being generated as a result of sweeping an electron beam around an arcuate anode. This allows images to be obtained more rapidly than in conventional scanners. However, because the electron source lies on the axis of rotation, such swept beam scanners are not compatible with conveyor systems which themselves pass close, and parallel, to the axis of rotation.


SUMMARY

The present specification discloses an X-ray scanning system for inspecting items, the system comprising an X-ray source extending around a scanning volume, and defining a plurality of source points from which X-rays can be directed through the scanning volume, an X-ray detector array also extending around the scanning volume and arranged to detect X-rays from the source points which have passed through the scanning volume and produce output signals dependent on the detected X-rays, and a conveyor arranged to convey the items through the scanning volume.


The present specification further discloses a networked inspection system comprising an X-ray scanning system, a workstation and connection means arranged to connect the scanning system to the workstation, the scanning system comprising an X-ray source extending around a scanning volume, and defining a plurality of source points from which X-rays can be directed through the scanning volume, an X-ray detector array also extending around the scanning volume and arranged to detect X-rays from the source points which have passed through the scanning volume and produce output signals dependent on the detected X-rays, and a conveyor arranged to convey the items through the scanning volume.


The present specification further discloses a sorting system for sorting items, the system comprising a tomographic scanner arranged to scan a plurality of scanning regions of each item thereby to produce a scanner output, analysing means arranged to analyse the scanner output and allocate each item to one of a plurality of categories at least partly on the basis of the scanner output, and sorting means arranged to sort items at least partly on the basis of the categories to which they have been allocated.


The present specification further discloses an X-ray scanning system comprising an X-ray source arranged to generate X-rays from a plurality of X-ray source positions around a scanning region, a first set of detectors arranged to detect X-rays transmitted through the scanning region, a second set of detectors arranged to detect X-rays scattered within the scanning region, and processing means arranged to process outputs from the first set of detectors to generate image data which defines an image of the scanning region, to analyse the image data to identify an object within the image, and to process the outputs from the second set of detectors to generate scattering data, and to associate parts of the scattering data with the object.


The present specification further discloses a data collecting system for collecting data from an X-ray scanner, the system comprising a memory having a plurality of areas each being associated with a respective area of an image, data input means arranged to receive input data from a plurality of X-ray detectors in a predetermined sequence, processing means arranged to generate from the input data X-ray transmission data and X-ray scattering data associated with each of the areas of the image, and to store the X-ray transmission data and the X-ray scattering data in the appropriate memory areas.


The present specification further discloses an X-ray scanning system comprising a scanner arranged to scan an object to generate scanning data defining a tomographic X-ray image of the object, and processing means arranged to analyse the scanning data to extract at least one parameter of the image data and to allocate the object to one of a plurality of categories on the basis of the at least one parameter.





BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the present invention will now be described by way of example only with reference to the accompanying drawings in which:



FIG. 1 is a longitudinal section of a real time tomography security scanning system according to a first embodiment of the invention;



FIG. 1a is a perspective view of an X-ray source of the system of FIG. 1;



FIG. 2 is a plan view of the system of FIG. 1;



FIG. 3 is a schematic side view of the system of FIG. 1;



FIG. 4 is a schematic diagram of a data acquisition system forming part of the system of FIG. 1;



FIG. 5 is a schematic diagram of a threat detection system forming part of the system of FIG. 1;



FIG. 6 is a schematic diagram of a baggage sorting system according to an embodiment of the invention including the scanning system of FIG. 1;



FIG. 7 is a schematic diagram of a baggage sorting system according to a further embodiment of the invention;



FIGS. 8a, 8b and 8c are schematic diagrams of baggage sorting systems according to further embodiments of the invention;



FIG. 9 is a schematic diagram of a networked baggage sorting system according to a further embodiment of the invention;



FIG. 10 is a schematic plan view of a stand-alone scanning system according to a further embodiment of the invention;



FIG. 11 is a schematic side view of the system of FIG. 10;



FIG. 12 is a schematic side view of a modular scanning system according to a further embodiment of the invention;



FIG. 13 is a diagram of an X-ray scattering event;



FIG. 14 is a longitudinal section through a security scanning system according to a further embodiment of the invention;



FIG. 15 is a further longitudinal section through the system of FIG. 14 showing how different scatter events are detected;



FIG. 16 is a transverse section through the system of FIG. 14;



FIG. 17 is a schematic diagram of a data acquisition system of the scanning system of FIG. 14;



FIG. 18 is a partial view of a dual energy scanner according to a further embodiment of the invention;



FIG. 19 is a further partial view of the scanner of FIG. 18;



FIG. 20 is a schematic view of a dual energy X-ray source of a further embodiment of the invention;



FIG. 21 is a schematic view of a detector array of a scanner according to a further embodiment of the invention;



FIG. 22 is a schematic view of a detector array of a scanner according to a further embodiment of the invention;



FIG. 23 is a circuit diagram of a data acquisition circuit of the embodiment of FIG. 21; and



FIG. 24 is a circuit diagram of a data acquisition circuit of a further embodiment of the invention.





DETAILED DESCRIPTION

The present specification discloses multiple embodiments. The following description is provided in order to enable a person having ordinary skill in the art to practice the invention. Language used in this specification should not be interpreted as a general disavowal of any one specific embodiment or used to limit the claims beyond the meaning of the terms used therein. The general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the invention. Also, the terminology and phraseology used is for the purpose of describing exemplary embodiments and should not be considered limiting. Thus, the present invention is to be accorded the widest scope encompassing numerous alternatives, modifications and equivalents consistent with the principles and features disclosed. For purpose of clarity, details relating to technical material that is known in the technical fields related to the invention have not been described in detail so as not to unnecessarily obscure the present invention.


Referring to FIGS. 1 to 3, a concourse baggage scanning system 6 comprises a scanning unit 8 comprising a multi-focus X-ray source 10 and X-ray detector array 12. The source 10 comprises a large number of source points 14 in respective spaced locations on the source, and arranged in a full 360° circular array around the axis X-X of the system. It will be appreciated that arrays covering less than the full 360° angle can also be used.


Referring to FIG. 1a, the X-ray source 10 is made up of a number of source units 11 which are spaced around the scanning region 16 in a substantially circular arrangement, in a plane perpendicular to the direction of movement of the conveyor. Each source unit 11 comprises a conductive metal suppressor 13 having two sides and an emitter element 15 extending along between the suppressor sides. A number of grid elements in the form of grid wires 17 are supported above the suppressor 13 perpendicular to the emitter element 15. A number of focusing elements in the form of focusing wires 19 are supported in another plane on the opposite side of the grid wires to the emitter element. The focusing wires 19 are parallel to the grid wires 17 and spaced apart from each other with the same spacing as the grid wires, each focusing wire 19 being aligned with a respective one of the grid wires 17.


The focusing wires 19 are supported on two support rails 21 which extend parallel to the emitter element 15, and are spaced from the suppressor 13. The support rails 21 are electrically conducting so that all of the focusing wires 19 are electrically connected together. One of the support rails 21 is connected to a connector 23 to provide an electrical connection for the focusing wires 19. Each of the grid wires 17 extends down one side of the suppressor 12 and is connected to a respective electrical connector 25 which provide separate electrical connections for each of the grid wires 17.


An anode 27 is supported above the grid wires 17 and focusing wires 19. The anode 27 is formed as a rod, typically of copper with tungsten or silver plating, and extends parallel to the emitter element 15. The grid and focusing wires 17, 19 therefore extend between the emitter element 15 and the anode 27. An electrical connector 29 provides an electrical connection to the anode 27.


The grid wires 17 are all connected to a negative potential, apart from two which are connected to a positive potential. These positive grid wires extract a beam of electrons from an area of the emitter element 15 and, with focusing by the focusing wires 19, direct the electron beam at a point on the anode 27, which forms the X-ray source point for that pair of grid wires. The potential of the grid wires can therefore be switched to select which pair of grid wires is active at any one time, and therefore to select which point on the anode 27 is the active X-ray source point at any time.


The source 10 can therefore be controlled to produce X-rays from each of the source points 14 in each of the source units 11 individually and, referring back to FIG. 1, X-rays from each source point 14 are directed inwards through the scanning region 16 within the circular source 10. The source 10 is controlled by a control unit 18 which controls the electrical potentials applied to the grid wires 17 and hence controls the emission of X-rays from each of the source points 14. Other suitable X-ray source designs are described in WO 2004/097889.


The multi-focus X-ray source 10 allows the electronic control circuit 18 to be used to select which of the many individual X-ray source points 14 within the multi-focus X-ray source is active at any moment in time. Hence, by electronically scanning the multi-focus X-ray tube, the illusion of X-ray source motion is created with no mechanical parts physically moving. In this case, the angular velocity of source rotation can be increased to levels that simply cannot be achieved when using conventional rotating X-ray tube assemblies. This rapid rotational scanning translates into an equivalently speeded up data acquisition process and subsequently fast image reconstruction.


The detector array 12 is also circular and arranged around the axis X-X in a position that is slightly offset in the axial direction from the source 10. The source 10 is arranged to direct the X-rays it produces through the scanning region 16 towards the detector array 12 on the opposite side of the scanning region. The paths 18 of the X-ray beams therefore pass through the scanning region 16 in a direction that is substantially, or almost, perpendicular to the scanner axis X-X, crossing each other near to the axis. The volume of the scanning region that is scanned and imaged is therefore in the form of a thin slice perpendicular to the scanner axis. The source is scanned so that each source point emits X-rays for a respective period, the emitting periods being arranged in a predetermined order. As each source point 14 emits X-rays, the signals from the detectors 12, which are dependent on the intensity of the X-rays incident on the detector, are produced, and the intensity data that the signals provide are recorded in memory. When the source has completed its scan the detector signals can be processed to form an image of the scanned volume.


A conveyor belt 20 moves through the imaging volume, from left to right, as seen in FIG. 1, parallel to the axis X-X of the scanner. X-ray scatter shields 22 are located around the conveyor belt 20 upstream and downstream of the main X-ray system to prevent operator dose due to scattered X-rays. The X-ray scatter shields 22 include lead rubber strip curtains 24 at their open ends such that the item 26 under inspection is dragged through one curtain on entering, and one on leaving, the inspection region. In the integrated system shown, the main electronic control system 18, a processing system 30, a power supply 32 and cooling racks 34 are shown mounted underneath the conveyor 20. The conveyor 20 is arranged to be operated normally with a continuous scanning movement at constant conveyor speed, and typically has a carbon-fibre frame assembly within the imaging volume.


Referring to FIG. 4 the processing system 30 includes an electronic data acquisition system and real-time image reconstruction system. The X-ray detector array 12 comprises banks of individual X-ray detectors 50 configured in a simple linear pattern (e.g. 1×16). Multiple ring patterns (e.g. 8×16) are also possible. Each detector 50 outputs a signal dependent on the intensity of the X-rays it detects. A multiplexing block 52 multiplexes the output data signals from each of the input X-ray detectors 50, performs data filtering, gain and offset corrections and formats the data into a high-speed serial stream. A selection block 53 takes input from all of the multiplexing blocks 52 and selects just the part of the entire X-ray data that is required for the image reconstruction. The selection block 53 also determines the un-attenuated X-ray beam intensity, Io, for the appropriate X-ray source point (which will vary for every X-ray source point within the multi-focus X-ray tube), processes the X-ray intensity data, Ix, from the multiplexing block 52 by forming the result loge(Ix/Io) and then convolves this with a suitable 1-D filter. The resulting projection data is recorded as a sinogram, in which the data is arranged in an array with pixel number along one axis, in this case horizontally, and source angle along another axis, in this case vertically. Data is then passed from the selection block 53 in parallel to a set of backprojection-summation processor elements 54. The processor elements 54 are mapped into hardware, using look-up tables with pre-calculated coefficients to select the necessary convolved X-ray data and weighting factors for fast backprojection and summation. A formatting block 55 takes the data representing individual reconstructed image tiles from the multiple processor elements 54 and formats the final output image data to a form suitable for generating a suitably formatted three dimensional image on a display screen. This output can be generated fast enough for the images to be generated in real time, for viewing in real time or off-line, hence the system is termed a real time tomography (RTT) system.


In this embodiment the multiplexing block 52 is coded in software, the selection block 53 and formatting block 55 are both coded in firmware, and the processor elements mapped in hardware. However, each of these components could be either hardware or software depending on the requirements of the particular system.


Referring to FIG. 5 each of the final output image for each baggage item is then processed by a threat detection processor 60 within the processing system 30 which is arranged to determine whether the imaged baggage item represents a threat. In the threat detection processor 60, input X-ray tomographic image data 62 is passed in to a set of low-level parameter extractors 63 (level 1). The parameter extractors 63 identify features in the image such as areas of constant grey level, texture and statistics. Some of the extractors work on the data for individual 2 dimensional images or slices, some work on the 3 dimensional images, and some work on the sonogram data. Where possible, each extractor works in parallel on the same set of input data, and each extractor is arranged to perform a different processing operation and to determine a different parameter. At the end of the processing, the parameters determined by the parameter extractors 63 are passed up to a set of decision trees 64 (level 2). Details of the parameters extracted are given below. The decision trees 64 each take a number (typically all) of the low level parameters and construct respective higher level information, such as information regarding contiguous volumes, with associated statistics. At the top level (level 3), a database searcher 65 maps the higher level parameters produced at level 2 into a ‘red’ probability Pr(threat) of there being a threat present and a ‘green’ probability Pr(safe) of the item under inspection being safe. These probabilities are used by the processing system 30 to allocate the scanned item to an appropriate safety category, and to produce an automatic sorting control output. This automatic sorting control output can be either a first ‘green’ output indicating that the item is allocated to a clear category, a second ‘red’ output indicating that the item is allocated to a ‘not clear’ category, or a third ‘amber’ output indicating that the automatic sorting cannot be carried out with sufficient reliability to allocated the item to the ‘clear’ or the ‘not clear’ category. Specifically if Pr(safe) is above a predetermined value, (or Pr(threat) is below a predetermined value) then the automatic sorting output will be produced having a first signal form, indicating that the item should be allocated to the green channel. If Pr(threat) is above a predetermined value, (or Pr(safe) is below a predetermined value) then the automatic sorting output will be produced having a second signal form, indicating that the item should be allocated to the red channel. If Pr(threat) (or Pr (safe)) is between the two predetermined values, then the automatic sorting output is produced having a third signal form, indicating that the item cannot be allocated to either the red or green channel. The probabilities can also be output as further output signals.


The parameters that will be determined by the parameter extractors 63 generally relate to statistical analysis of pixels within separate regions of the 2-dimensional or 3-dimensional image. In order to identify separate regions in the image a statistical edge detection method is used. This starts at a pixel and then checks whether adjacent pixels are part of the same region, moving outwards as the region grows. At each step an average intensity of the region is determined, by calculating the mean intensity of the pixels within the region, and the intensity of the next pixel adjacent to the region is compared to that mean value, to determine whether it is close enough to it for the pixel to be added to the region. In this case the standard deviation of the pixel intensity within the region is determined, and if the intensity of the new pixel is within the standard deviation, then it is added to the region. If it is not, then it is not added to the region, and this defines the edge of the region as being the boundary between pixels in the region and pixels that have been checked and not added to the region.


Once the image has been divided into regions, then parameters of the region can be measured. One such parameter is a measure of the variance of the pixel intensity within the region. If this is high this might be indicative of a lumpy material, which might for example be found in a home-made bomb, while if the variance is low this would be indicative of a uniform material such as a liquid.


Another parameter that is measured is the skewedness of the distribution of pixel value within the region, which is determined by measuring the skewedness of a histogram of pixel values. A Gaussian, i.e. non-skewed, distribution indicates that the material within the region is uniform, whereas a more highly skewed distribution indicates non-uniformities in the region.


As described above, these low-level parameters are passed up to the decision trees 64, where higher level information is constructed an higher level parameters determined. One such higher level parameter is the ratio of the surface area to the volume of the identified region. Another is a measure of similarity, in this case cross-correlation, between the shape of the region and template shapes stored in the system. The template shapes are arranged to correspond to the shape of items that pose a security threat, such as guns or detonators. These high level parameters are used as described above to determine a level if threat posed by the imaged object.


Referring to FIG. 6 an in-line real time tomography baggage sorting system comprises the scanning system 6 of FIG. 1 with the conveyor 20 passing through it. Downstream of the scanning system 6 a sorting device 40 is arranged to receive articles of baggage from the conveyor 20 and move them onto either a clear or ‘green’ channel conveyor 42 or a not clear or ‘red’ channel conveyor 44. The sorting device 40 is controlled by the automatic sorting output signals via a control line 46 from the processing system 30, which are indicative of the decision of the processing system 30 as to whether the item is clear or not, and also by signals from a workstation 48 to which it is connected via line 45. The images from the scanning system 6 and signals from the processing system 30, indicative of the red and green probabilities and the nominal decision of the processing system 30, are also fed to the workstation 48. The workstation is arranged to display the images on a screen 47 so that they can be viewed by a human operator, and also to provide a display indicative of the green and red probabilities and the nominal automatic sorting decision. The user at the workstation can review the images and the probabilities, and the automatic sorting output, and decide whether to accept or override the decision of the scanning system, if that was to allocate the item to the red or green category, or to input a decision if the scanning system decision was to allocate the item to the ‘amber’ category. The workstation 48 has a user input 49 that enables the user to send a signal to the sorting device 40 which can be identified by the sorting device as over-riding the decision of the scanning system. If the over-riding signal is received by the sorting device, then the sorting device does over-ride the decision of the scanning system. If no over-ride signal is received, or indeed if a confirming signal is received from the workstation confirming the decision of the scanning system, then the sorting device sorts the item on the basis of the decision of the scanning system. If the sorting system receives an ‘amber’ signal from the scanning system relating to an item, then it initially allocates that item to the ‘red’ category to be put into the red channel. However, if it receives an input signal from the workstation before it sorts the item indicating that it should be in the ‘green’ category, then it sorts the item to the green channel.


In a modification to the system of FIG. 6, the sorting can be fully automatic, with the processing system giving one of just two sorting outputs, ‘clear’ and ‘not clear’, allocating the item to either the green or the red channel. It would also be possible for the processing system to determine just one probability Pr(threat) with one threshold value and allocate the item to one of the two categories depending on whether the probability is above or below the threshold. In this case the allocation would still be provisional and the operator would still have the option of overriding the automatic sorting. In a further modification the automatic category allocation of the scanning system is used as the final allocation, with no user input at all. This provides a fully automated sorting system.


In the system of FIG. 6, the scan speed is matched to the conveyor velocity, so that the baggage can be moved at a constant velocity from a loading area where it is loaded onto the conveyor 20, through the scanning system 6, and on to the sorting device 40. The conveyor 20 extends for a distance L, between the exit of the scanning system 6 and the sorting device 40. During the time that a baggage item takes to travel the distance L on the conveyor 20, an operator can view the image data of the item under inspection, and the initial category allocation determined by the scanning system, and confirm or reject the automated decision of the RTT system. Typically the baggage would then be either accepted into the Clear channel and passed forward ready for transportation or rejected into the Not Cleared channel for further investigation.


In this RTT multi-focus system, the RTT scanning unit 8 is able to operate at full baggage belt speed, and hence no baggage queuing or other divert mechanism is required for optimal system operation. In integrated systems such as this, the limited throughput capability of conventional rotating source systems is a significant constraint. Often this means placing multiple conventional CT machines in parallel, and using sophisticated baggage handling systems to switch the item for inspection to the next available machine. This complexity can be avoided with the arrangement of FIG. 6.


Referring to FIG. 7 a second embodiment of the invention comprises a redundant system in which two RTT scanning systems 70, 72 are located in series on the same conveyor 74 such that if one system were to be taken out of service, then the other could continue to scan baggage. In either case, the conveyor belt 74 would continue to run through both scanning systems 70, 72 at standard operating belt speed.


Referring to FIG. 8a in a third embodiment there is provided a more complex redundant system in which two RTT systems 82, 84 are operated in parallel. A first main incoming conveyor 86 brings all items to be sorted to a first sorting device 88 which can transfer items onto either one of two further conveyors 90, 92. Each of these two conveyors 90, 92 passes through a respective one of the scanning systems 82, 84, which will scan the items and enable a decision to be made as to whether to clear the item or not. A further sorting device 94, 96 is provided on each of the two conveyors 90, 92 which is arranged to sort the baggage onto a common ‘green channel’ conveyor 98 for onward transportation, or a ‘red channel’ conveyor 100 if it is not cleared, where it can undergo further investigation. In this configuration, it is possible to run the input conveyor 86, and the ‘green channel’ conveyor at a higher speed than the RTT conveyor speed, typically up to twice the speed. For example in this case the main incoming conveyor 86 and the common ‘green channel’ conveyor move at a speed of 1 m/s whereas the scanning conveyors 82, 84 travel at half that speed, i.e. 0.5 m/s. Of course the system can be expanded with more parallel RTT systems, with the ratio of the speed of the main incoming conveyor to that of the scanner conveyors being equal to, or substantially equal to, the number of parallel scanners, although the sorting devices may become unreliable at more than about 1 m/s main conveyor speed.


Referring to FIG. 8b, in a further embodiment a baggage sorting system comprises a number of RTT scanners 81b, 82b, 83b, typically up to about 60 in one system, each associated with a respective check-in desk. A sorting device 84b, 85b, 86b is associated with each RTT scanner, and baggage is conveyed on a conveyor from each RTT scanner to its associated sorting device. Each sorting device 84b, 85b, 86b sorts the baggage, in response to signals from its scanner, onto either a common clear channel conveyor 88b, or a common reject channel conveyor 87b. A further backup RTT scanner 89b is provided on the reject channel conveyor 87b, with an associated sorting device 90b, that can leave baggage on the reject channel conveyor 87b, or transfer it to the clear channel conveyor 88b.


Under normal operation, each of the primary scanners 81b, 82b, 83b sorts the baggage, and the backup or redundant scanner 89b simply provides a further check on items sorted into the reject channel. If that scanner determines that an item of baggage represents no, or a sufficiently low threat, then it transfers it to the clear channel. If one of the primary scanners is not functioning or has a fault, then its associated sorting device is arranged to sort all baggage from that scanner to the reject channel. Then, the back-up scanner 89b scans all of that baggage and controls sorting of it between the clear and reject channels. This enables all the check-in desks to continue to function while the faulty scanner is repaired or replaced.


Referring to FIG. 8c, in a further embodiment, baggage from each of the check-in desks is transferred via a plurality of separate conveyors onto a central loop or carousel 81c, on which it circulates continuously. A number of sorting devices 82c, 83c, 84c are each arranged to transfer items of baggage from the loop 81c to a respective conveyor leading to a respective RTT scanner 85c, 86c, 87c. The sorting devices 82c, 83c, 84c are controlled by the scanners to control the rate at which baggage items are fed to each of the scanners. From the scanners, conveyors transfer all of the baggage items to a common exit conveyor 88c leading to a further sorting device 89c. This is controlled by all of the scanners to sort each of the baggage items between a clear channel 90c and a reject channel 91c.


In order to track the movement of each item of baggage, each item is given a 6-digit ID, and its position on the conveyor recorded when it first enters the system. The scanners can therefore identify which item of baggage is being scanned at any one time, and associate the scanning results with the appropriate item. The sorting devices can therefore also identify the individual baggage items and sort them based on their scanning results.


The number of scanners and the speeds of the conveyors in this system are arranged such that, if one of the scanners is not functioning, the remaining scanners can process all of the baggage that is being fed onto the loop 81c from the check-in desks.


In a modification to this embodiment, the sorting devices 82c, 83c, 84c that select which items are transferred to each scanner are not controlled by the scanners, but are each arranged to select items from the loop 81c so as to feed them to the respective scanner at a predetermined rate.


Referring to FIG. 9 a networked system according to a further embodiment comprises three scanning systems 108 similar to that of FIG. 6, and four operator workstations 148. The video image outputs from the three RTT scanning systems 108 are connected via respective high bandwidth point-to-point video links to real time disk arrays 109 which providing transient storage for the raw image data, to a redundant video switch 110. The disk arrays 109 are in turn connected to each of the workstations 148. The video switch 110 is therefore able to transmit the raw video image output from each of the scanning systems 108 from its temporary storage, to any one of the workstations 148, where it can be used to create 3-dimensional video images which can be viewed off-line. The outputs from the scanning system for the red/green probability signals and the automatic sorting allocation signals are connected to a redundant conventional Ethernet switch 112, which is also connected to each of the workstations. The Ethernet switch is arranged to switch each of the probability signals and the sorting allocation signals to the same workstation 148 as the associated video signal. This allows image data from the multiple machines together with the automatic allocation and probabilities assigned to the allocation, to be switched through to the bank of operator workstations 148 where an operator can both monitor the performance of the baggage inspection system and determine the destination of baggage assigned an amber threat level.


Alternatively, a networked system comprises a single scanning system 108 connected to a server and a workstation 148. The video image output from the scanning system 108 is connected to a real time disk array 109, which provides transient storage for the raw image data. The disk array 109 is in turn connected to the workstation 148. The probability signal and allocation signal outputs are sent to the workstation 148 together with the associated video image output to be monitored by an operator. The networked single scanning system may be part of a networked system with multiple scanning systems.


Referring to FIGS. 10 and 11, in a further embodiment an in-line scanner has a conveyor belt 160 just as long as the main scatter shields 162. In such standalone system configurations, the item for inspection is placed onto the conveyor belt 160 and the item loaded into the system. The item is then scanned through the scanner machine 164 and images are generated. Often, in conventional systems, the item is pre-screened with a simple transmission X-ray system to identify likely threat areas prior to computed tomography screening of selected planes in the object. Such applications are simple for a real-time multi-focus system to cope with. Here, no pre-screening would be used and a true three-dimensional image of the complete item would be obtained.


In some embodiments the locus of source points in the multi-focus X-ray source will extend in an arc over an angular range of only 180 degrees plus the fan beam angle (typically in the range 40 to 90 degrees). The number of discrete source points is advantageously selected to satisfy the Nyquist sampling theorem. In some embodiments, as in that of FIG. 1, a complete 360 degree ring of source points is used. In this case, the dwell-time per source point is increased over a 180+fan beam configuration for a given scan rate and this is advantageous in improving reconstructed image signal-to-noise ratio.


The scanner system of FIG. 1 is an integrated scanner system, in that the control, processing, power supply, and cooling units 18, 30, 32, 34 are housed in a unit with the scanning system 8 and the screening 22. Referring to FIG. 12, in a further embodiment there is provided a modular system in which some, or all, of the control, processing, power supply, and cooling racks 218, 230, 232, 234 are located remotely from the scanning unit 208 comprising multi-focus X-ray source and sensor array. It is advantageous to use a modular design to facilitate easy installation, particularly in baggage handling hall environments, where systems may be suspended from the ceiling or in regions with restricted access. Alternatively, a complete system can be configured as an integrated unit with the sub-assembly units co-located within a single housing.


In some embodiments, including that of FIG. 1, a single X-ray detector ring is used. This is inexpensive to construct and provides adequate signal-to-noise performance even at high image scanning rates with a simple fan-beam image reconstruction algorithm. In other embodiments (particularly for large image reconstruction circle diameter) it is preferable to use a multi-ring sensor array with a plurality of circular or part-circular groups of sensors arranged adjacent to each other, spaced along the axis of the system offset from the source. This enables a more complex cone-beam image reconstruction algorithm to be used in the processing system. The use of a multi-ring sensor increases dwell-time per source point resulting in larger integrated signal size and consequent improvement in signal-to-noise ratio in the reconstructed image.


Central to the design of the embodiments described above, which use a multi-focus X-ray source based computed tomography system, is the relationship between the angular rotational speed of the source and the velocity of the conveyor system passing through the scanner. In the limit that the conveyor is stationary, the thickness of the reconstructed image slice is determined entirely by the size of the X-ray focus and the area of the individual elements of the X-ray detector array. As conveyor speed increases from zero, the object under inspection will pass through the imaging slice during rotation of the X-ray beam and an additional blurring will be introduced into the reconstructed image in the direction of the slice thickness. Ideally, the X-ray source rotation will be fast compared to the conveyor velocity such that blurring in the slice thickness direction will be minimised.


A multi-focus X-ray source based computed tomography system for baggage inspection provides a good ratio of angular source rotational speed to linear conveyor speed for the purposes of high probability detection of threat materials and objects in the item under inspection. As an example, in the embodiment of FIG. 1, the conveyor speed is 0.5 m/s as is common in airport systems. The source can achieve 240 source rotations about the conveyor per second, so the object under inspection will move a distance of 2.08 mm through the imaging slice during the scan. In a conventional system with source rotation of 4 revolutions per second, the object under inspection will move a distance of 62.5 mm through the imaging slice during the scan at the same belt speed.


The primary goal of an inspection system for detection of threat materials is to detect accurately the presence of threat materials and to pass as not suspect all other materials. The larger the blurring in the slice direction that is caused by conveyor motion during a scan, the greater the partial volume artefact in the reconstructed image pixel and the less accurate the reconstructed image density. The poorer the accuracy in the reconstructed image density, the more susceptible the system is to provide an alarm on non-threat materials and to not raise an alarm on true threat materials. Therefore, a real-time tomography (RTT) system based on multi-focus X-ray source technology can provide considerably enhanced threat detection capability at fast conveyor speeds than conventional mechanically rotated X-ray systems.


Due to the use of an extended arcuate anode in a multi-focus X-ray source, it is possible to switch the electron source such that it jumps about the full length of the anode rather than scanning sequentially to emulate the mechanical rotation observed in conventional computed tomography systems. Advantageously, the X-ray focus will be switched to maximise the distance of the current anode irradiation position from all previous irradiation positions in order to minimise the instantaneous thermal load on the anode. Such instantaneous spreading of the X-ray emission point is advantageous in minimising partial volume effect due to conveyor movement so further improving reconstructed pixel accuracy.


The high temporal resolution of RTT systems allows a high level of accuracy to be achieved in automated threat detection. With this high level of accuracy, RTT systems can be operated in unattended mode, producing a simple two-state output indication, with one state corresponding to a green or clear allocation and the other to a red or not clear allocation. Green bags are cleared for onward transport. Red bags represent a high level of threat and should be reconciled with the passenger and the passenger barred from travelling.


Further embodiments of the invention will now be described in which data relating to the scattering of X-rays as well as that relating to transmitted X-rays is recorded and used to analyse the scanned baggage items.


Referring to FIG. 13 when a beam 300 of X-rays passes through an object 302, some of the X-rays are transmitted straight through it, and exit the object travelling in the same direction as they entered it. Some of the X-rays are scattered through a scattering angle θ, which is the difference between the direction in which they enter the object and the direction in which they leave it. As is well known there are two types of scattering that occur: coherent or Bragg scattering, which is concentrated around scattering angles of 5°, typically in the range 4° to 6°, and incoherent or Compton scattering in which the X-ray is scattered through larger angles. Bragg scattering increases linearly with the atomic number of the object and obeys the formula:

nλ=2d sin θ

where n is an integer, λ is the wavelength of the X-ray, and d is the inter-atomic distance in the object.


Therefore the amount of Bragg scattering gives information about the atomic structure of the object. However, it does not vary smoothly with atomic number.


The amount of Compton scattering is dependent on, and varies smoothly with, the electron density of the object, and therefore the amount of scattering at higher scatter angles gives information about the electron density of the object, and hence about its atomic number.


Referring to FIG. 14 a security scanning system according to a further embodiment of the invention comprises a multi-focus X-ray source 410 which is the same as that of FIG. 1, and a circular detector array 412 and conveyor 420 that are also the same as those of FIG. 1. However, in this embodiment, the system comprises a further cylindrical array of detectors 422 which also extends around the conveyor at the same radius as the circular detector array 412 but on the other side axially of the source 410. Whereas the circular detector array is arranged to detect X-rays transmitted through the object 426, the cylindrical detector array 422 is arranged to detect X-rays scattered in the object. The scatter detector array 422 is made up of a number of circular arrays or rings 422a, 422b of detectors, and the detectors in each ring are equally spaced around the conveyor so that they are arranged in a number of straight rows extending in the axial direction of the scanner.


The detectors in the scatter detector array 422 are energy resolving detectors such that individual X-ray interactions with each detector produce a detector output that is indicative of the energy of the X-ray. Such detectors can be fabricated from wide bandgap III-V or II-IV semiconductor materials such as GaAs, HgI, CdZnTe or CdTe, a narrow gap semiconductor such as Ge, or a composite scintillation detector such as NaI(Ti) with photomultiplier tube readout.


Referring to FIG. 15, a collimator 428 is provided in front of the scattering detectors 422. The collimator 428 provides a barrier that prevents X-rays from reaching each detector unless it comes from a particular receiving direction. For each detector in the array 422, the receiving direction passes through the central longitudinal axis X-X of the scanner, as can be seen in FIG. 16. However, the receiving direction is not perpendicular to the axis X-X, but is inclined at about 5° to the plane of the detector rings 422a, 422b in the direction towards the source 410, as can be seen in FIG. 15.


Referring to FIG. 15 it will be appreciated that X-rays incident on any one of the detectors of the array 422 must have been scattered from a respective small sub-volume within the thin imaged volume that lies both in the path of the X-ray beam and in the line of the receiving direction from the detector 422. For any coherently scattered X-rays, the axial position of the detector that detects it will be determined by the distance from the active X-ray source point at which the scattering occurred. Detectors nearest the source 410 in the axial direction will detect X-rays scattered furthest from the active X-ray source point. For example X-rays scattered from the point x, which is nearest the active X-ray source point 410a, will be detected by a detector further from the source 410 than X-rays scattered from the point z which is further from the active X-ray source point. Therefore, at any one time, when the active X-ray source point can be identified, the axial position of the detector which detects the scattered X-ray can be used to determine the position of the scattering along the X-ray beam direction.


It will also be appreciated from FIG. 15 that, for this system to work, it is important that the X-ray beam should be narrowly focused in the axial direction of the scanner. Spreading of the beam in the transverse direction, e.g. use of a fan beam spread in the transverse direction will still allow this positioning of coherent scattering events.


Referring to FIG. 16, because the collimator 428 is directed towards the axis of the scanner, X-rays from an active source point 410a that undergo coherent scattering will only be detected by the row of detectors 422a that is on the opposite side of the scanner axis to the active source point, and possibly one or more of the rows close to it on either side depending on how narrowly focussed the collimator is. If X-rays are confined to a straight narrow ‘pencil’ beam, then any X-rays that are scattered incoherently through larger angles will not be detected at all as they will be cut off by the collimator 428. An example of such an X-ray is shown by arrow ‘a’ in FIG. 16. However, if a fan beam of X-rays is produced from the active source point 410a, that is spread out through the imaging volume slice in the direction perpendicular to the scanner axis, then X-rays directed further away from the scanner axis can undergo incoherent scattering and reach detectors to either side of the row 422a opposite the active source point. Examples of such X-rays are shown by the arrows b and c. It will be noted that, to reach any detector 422b, the scattering event must take place in the plane passing through the scanner axis and that detector 422b. This means that, for a given active source point and a particular detector, the position of the scattering event of a detected X-ray can be identified as being in the plane passing through the scanner axis and that detector. If the exact position of the scattering event is to be determined then other information is needed. For example if information regarding the position of objects within the imaging volume is available, for example from tomographic imaging data, then the scattering can be associated with the most likely object as will be described in more detail below.


From the Bragg scattering data, for each detected scattering event, the combination of the X-ray energy and the scatter angle can be used to determine the inter-atomic distance d of the material in which the scattering event took place. In practice, the scatter angle can be assumed to be constant, and the energy used to distinguish between different materials. For the Compton scattering, the level of scattering from each volume of the scanning volume gives an indication of the density of the material in that volume. The ratio of Compton to coherent scatter can also be determined and used as a further parameter to characterise the material of the imaged object.


Due to the short dwell time for each X-ray source point, the number of detected scattered X-rays for each source point will always be very low, typically less than five. In order to form a reasonable coherent scatter signal it is necessary to collect scatter data for all source points within a tomographic scan and then accumulate the results for each sub-volume of the imaging volume. For a scanner with 500 source points, and an average of one coherent diffraction scatter result per sub-volume per scan, then following accumulation of the set of data, each sub-volume will have 500 results associated with it, corresponding to 500 scattering events within that sub-volume. A typical sub-volume occupies an area within the imaging plane of a few square centimeters, with a volume thickness of a few millimetres.


Referring to FIG. 17, the data acquisition system arranged to accumulate data from the scatter detector array 422 of the scanner of FIGS. 14 to 16 comprises a multi-channel analyser 500 associated with each of the detectors 422. Each MCA 500 is arranged to receive the output signals from the detector, and allocate each X-ray detected to one of a number of X-ray energy ranges or channels, and output a signal indicative of the energy range in which the detected X-ray falls. A multiplexer 502 is arranged to receive the outputs from each of the MCAs 500. A look-up table 504 is also provided which has entries in it that, for a given source point and detector, identify the sub-volume within the imaging volume in which the X-ray was scattered. The system further comprises an image memory 506 which includes a number of memory areas 508, each of which is associated with a respective sub-volume within the scanner imaging plane.


Data is loaded into each memory area 508 automatically by the multiplexer 502 under the direction of the look up table 504. The look up table is loaded with coefficients prior to scanning that map each combination of detector 422 and MCA 500 to a respective image location 508, one look up table entry per X-ray source position. Those pixels, i.e. detectors 422, that are in the forward direction, i.e. substantially in the direction that the photon is travelling from the source prior to any interaction, are assumed to record coherent scatter photons at small beam angles of about 4-6 degrees. Those pixels 422 that are not in the forward direction are assumed to record incoherent scattered photons due to the Compton scattering effect. Hence, the image memory 506 is actually “three dimensional”—two dimensions represent location in the image while the third dimension holds scattered energy spectra for both coherent (lo 8-bits) and incoherent scattering (hi 8 bits). The look up table 504 will also instruct the multiplexer 502 as to the type of data that is being collected for each MCA 500 at each projection so that the appropriate memory space is filled.


Once the scatter data has been collected for a given scan, the data is transferred to and synchronised, by a projection sequencer 510, with the main RTT data acquisition system 512, which is described above with reference to FIG. 4. Hence the reconstructed image data and scatter data are passed through simultaneously to the threat detection system, which can use it to determine suitable parameters for analysis.


For each scan, the tomographic image data from the transmission detectors 412 produces data relating to the X-ray attenuation for each pixel of the image, which in turn corresponds to a respective sub-volume of the tomographic imaging volume. This is obtained as described above with reference to FIG. 4. The data from the scatter detectors 422 provides, as described above, data relating to the amount of coherent scattering within each sub-volume, and data relating to the amount of incoherent scattering within each sub-volume. This data can therefore be analysed in a threat detection processor similar to that of FIG. 5. In this case the parameters of the data which are extracted can relate to the image data or the scatter data or combinations of two or more types of data. Examples of parameters that are extracted from the data are the ratio of coherent to incoherent scatter, material types as determined from coherent scatter data, material density as determined from incoherent scatter data, correlation of CT image pixel values with scatter data. Also parameters for the scatter data corresponding to those described above for the transmission data can also be determined.


Referring to FIG. 18, in a further embodiment of the invention the transmission detectors 512 that are used to generate the tomographic image data are arranged to measure the X-ray transmission over different energy ranges. This is achieved by having two sets of detectors 512a, 512b, each forming a ring around the conveyor. The two sets are at different axial locations along the direction of travel of the conveyor, in this case being adjacent to each other in the axial direction. The first set 512a has no filter in front of it, but the second set 512b has a metal filter 513 placed between it and the X-ray source 510. The first set of detectors 512a therefore detects transmitted X-rays over a broad energy range, and the second set 512b detects X-rays only in a narrower part of that range at the high energy end.


As the item to be scanned moves along the conveyor, each thin volume or slice of it can be scanned once using the first set of detectors 512a and then scanned again using the second set 512b. In the embodiment shown, the same source 510 is used to scan two adjacent volumes simultaneously, with data for each of them being collected by a respective one of the detector sets 512a, 512b. After a volume of the item has moved past both sets of detectors and scanned twice, two sets of image data can be formed using the two different X-ray energy ranges, each image including transmission (and hence attenuation) data for each pixel of the image. The two sets of image data can be combined by subtracting that for the second detector set 512a from that of the first 512b, resulting in corresponding image data for the low energy X-ray component.


The X-ray transmission data for each individual energy range, and the difference between the data for two different ranges, such as the high energy and low energy, can be recorded for each pixel of the image. The data can then be used to improve the accuracy of the CT images. It can also be used as a further parameter in the threat detection algorithm.


It will be appreciated that other methods can be used to obtain transmission data for different ranges of X-ray energies. In a modification to the system of FIGS. 18 and 19, balanced filters can be used on the two detector sets. The filters are selected such that there is a narrow window of energies that is passed by both of them. The image data for the two sets of detectors can then be combined to obtain transmission data for the narrow energy window. This enables chemical specific imaging to be obtained. For example it is possible to create bone specific images by using filters balanced around the calcium K-edge energy. Clearly this chemical specific data can be used effectively in a threat detection algorithm.


In a further embodiment, rather than using separate filters, two sets of detectors are used that are sensitive to different energy X-rays. In this case stacked detectors are used, comprising a thin front detector that is sensitive to low energy X-rays but allows higher energy X-rays to pass through it, and a thick back detector sensitive to the high energy X-rays that pass through the front detector. Again the attenuation data for the different energy ranges can be used to provide energy specific image data.


In a further embodiment two scans are taken of each slice of the object with two different X-ray beam energies, achieved by using different tube voltages in the X-ray source, for example 160 kV and 100 kV. The different energies result in X-ray energy spectra that are shifted relative to each other. As the spectra are relatively flat over part of the energy range, the spectra will be similar over much of the range. However, part of the spectrum will change significantly. Therefore comparing images for the two tube voltages can be used to identify parts of the object where the attenuation changes significantly between the two images. This therefore identifies areas of the image that have high attenuation in the narrow part of the spectrum that changes between the images. This is therefore an alternative way of obtaining energy specific attenuation data for each of the sub-volumes within the scanned volume.


Referring to FIG. 20 in a further embodiment of the invention, two different X-ray energy spectra are produced by providing an anode 600 in the X-ray tube that has target areas 602, 604 of two different materials. In this case, for example, the anode comprises a copper base 606 with one target area 602 of tungsten and one 604 of uranium. The electron source 610 has a number of source points 612 that can be activated individually. A pair of electrodes 612, 614 is provided on opposite sides of the path of the electron beam 616 which can be controlled to switch an electric field on and off to control the path of the electron beam so that it strikes either one or the other of the target areas 602, 604. The energy spectrum of the X-rays produced at the anode will vary depending on which of the target areas is struck by the electron beam 616.


This embodiment uses an X-ray source similar to that of FIG. 1a, with the different target areas formed as parallel strips extending along the anode 27. For each active electron source point two different X-ray spectra can be produced depending on which target material is used. The source can be arranged to switch between the two target areas for each electron source point while it is active. Alternatively the scan along the anode 27 can be performed twice, once for one target material and once for the other. In either case further electron beam focusing wires may be needed to ensure that only one or the other of the target materials is irradiated by the electron beam at one time.


Depending on the angle at which the X-ray beam is extracted from the anode, the beams from the two target areas 602, 604 can in some cases be arranged to pass though the same imaging volume and be detected by a common detector array. Alternatively they may be arranged to pass through adjacent slices of the imaging volume and detected by separate detector arrays. In this case the parts of the imaged item can be scanned twice as the item passes along the conveyor in a similar manner to the arrangement of FIG. 18.


Referring to FIG. 21, in a further embodiment, two detector arrays are provided in a single scanner, adjacent to each other in the axial direction, one 710 corresponding to that of FIG. 1 and being arranged to form a RTT image, and the other, 712, being of a higher resolution, and being arranged to produce a high resolution projection image of the scanned object. In this embodiment the high resolution detector array 712 comprises two parallel linear arrays 714, 716 each arranged to detect X-rays at a different energy, so that a dual energy projection image can be produced. In the embodiment of FIG. 22, the high resolution array 812 comprises two stacked arrays, a thin array on top arranged to detect lower energy X-rays but transparent to higher energy X-rays, and a thicker array beneath arranged to detect higher energy X-rays. In both cases, the two detector arrays are arranged close enough together in the axial direction to be able to detect X-rays from a single linear array of source points.


In order to provide a projection image, data needs to be captured from all of the detectors in the high resolution array 712, 812 when only one source point is active. Referring to FIG. 23, in order to do this each detector 718, 818 in the high resolution array is connected to an integrator 750. The integrator comprises an amplifier 752 in parallel with a capacitor 754. An input switch 756 is provided between the detector 718 and the amplifier 752, a reset switch 758 is provided across the input terminals of the amplifier, and a further reset switch 759 connected across the capacitor 754, and a multiplexing switch 760 is provided between the integrator and an analogue to digital converter ADC.


In operation, while the detector 718 is not required to be active, all of the switches except for the multiplexing switch 760 are closed. This ensures that the capacitor 754 is uncharged and remains so. Then, at the start of the period when the detector is required to gather data, the two reset switches 758, 759 are closed so that any X-rays detected by the detector 718 will cause an increase in the charge on the capacitor 754, which results in integration of the signal from the detector 718. When the period for data collection has ended, the input switch 756 is opened, so that the capacitor will remain charged. Then, in order for the integrated signal to be read from the integrator, the output switch 760 is closed to connect the integrator to the ADC. This provides an analogue signal to the ADC determined by the level of charge on the capacitor 754, and therefore indicative of the number of X-rays that have been detected by the detector 718 during the period for which it was connected to the integrator. The ADC then converts this analogue signal to a digital signal for input to the data acquisition system. To produce a single projection image, all of the high resolution detectors are used to collect data at the same time, when one of the X-ray source points is active.


Referring to FIG. 24, in a further embodiment, each detector 718 is connected to two integrators 750a, 750b in parallel, each of which is identical to that of FIG. 23. The outputs from the two integrators are connected via their output switches 760a, 760b to an ADC. This enables each integrator to be arranged to integrate the signal from the detector 718 at a different point in the scan of the X-ray source, and therefore to collect data for a separate image, the two images being from different angles with different X-ray source points. For example this can be used to produce projection images from orthogonal directions which can be used to build up a high resolution 3-dimensional image, from which the position of features in the imaged package can be determined in three dimensions. The high resolution image can be useful when combined with the RTT image, as it can help identify items for which higher resolution is needed, such as fine wires.


The above examples are merely illustrative of the many application of the embodiments disclosed herein. Although only a few embodiments of the present invention have been described herein, it should be understood that the present invention might be embodied in many other specific forms without departing from the spirit or scope of the invention. Therefore, the present examples and embodiments are to be considered as illustrative and not restrictive, and the invention may be modified within the scope of the appended claims.

Claims
  • 1. An X-ray imaging system for scanning an object, the system comprising: stationary X-ray sources configured at least partially around an imaging volume;detectors configured at least partially around the imaging volume, wherein the detectors are configured to detect X-rays emitted from the stationary X-ray sources and are configured to generate X-ray image data;at least one processor configured to execute programmatic instructions that, when executed, receive the X-ray image data and generate at least a tomographic image from the X-ray image data, wherein the at least one processor is further configured to execute the programmatic instructions to: determine a plurality of parameters from the X-ray image data;apply one or more decision trees to the determined plurality of parameters to generate an output;construct information based on the output;determine if the information is indicative of a threat;allocate the object to a category indicative of safety based on a probability of the threat being present; andcause the object to be automatically sorted based on the category.
  • 2. The X-ray imaging system of claim 1, wherein the information comprises an extent of volume contiguity.
  • 3. The X-ray imaging system of claim 1, wherein the plurality of parameters comprise at least one of a constant gray level of the X-ray image data or a texture of the X-ray image data.
  • 4. The X-ray imaging system of claim 1, wherein the X-ray image data comprises data representative of two-dimensional images and wherein the plurality of parameters are determined from at least one of the two-dimensional images and the tomographic image.
  • 5. The X-ray imaging system of claim 1, wherein the plurality of parameters comprise more than one parameter and wherein the at least one processor is configured to execute the programmatic instructions that, when executed, determine, from the X-ray image data, each of the more than one parameter in parallel.
  • 6. The X-ray imaging system of claim 1, wherein the at least one processor is configured to execute the programmatic instructions that, when executed, cause the object to be automatically sorted into at least one of clear or not clear based on the category.
  • 7. The X-ray imaging system of claim 1, wherein each of the detectors is positioned in two or more detector arrays and wherein each of the two or more detector arrays is configured in a form of a linear array of detectors.
  • 8. The X-ray imaging system of claim 1, wherein the at least one processor is configured to execute the programmatic instructions that, when executed, identify one or more separate regions within the tomographic image by calculating a mean X-ray intensity of a set of pixels within the tomographic image, determining a standard deviation of X-ray intensities of the set of pixels, determining an X-ray intensity of a pixel proximate to the set of pixels, and adding the pixel to the set of pixels to form a region if the X-ray intensity of the pixel is within the standard deviation.
  • 9. The X-ray imaging system of claim 1, wherein the at least one processor is configured to execute the programmatic instructions that, when executed, identify one or more separate regions within the tomographic image by calculating a mean X-ray intensity of a set of pixels within the tomographic image, determining an X-ray intensity of a pixel adjacent to the set of pixels, comparing the X-ray intensity of the pixel to the mean X-ray intensity of the set of pixels, and adding the pixel to the set of pixels to form a region based on said comparing.
  • 10. The X-ray imaging system of claim 1, wherein the at least one processor is configured to execute the programmatic instructions that, when executed, identify a region of the tomographic image by defining an initial area of the region, identifying a pixel outside the initial area, determining a first value associated with the pixel, determining a corresponding second value of the initial area, comparing the first value and second value, and if a predetermined relationship is found between the first value and second value, including the pixel in the region.
  • 11. The X-ray imaging system of claim 10, wherein the first value and second value are X-ray intensity values.
  • 12. The X-ray imaging system of claim 10, wherein the predetermined relationship comprises an X-ray intensity of the pixel being within a predetermined range of an average X-ray intensity of the initial area.
  • 13. The X-ray imaging system of claim 1, wherein the at least one processor is configured to execute the programmatic instructions that, when executed, identify one or more separate regions within the tomographic image by using a statistical edge detection method.
  • 14. The X-ray imaging system of claim 1, wherein extracting a plurality of parameters from the X-ray tomographic image data comprises measuring a variance of a pixel intensity within one or more regions of the X-ray tomographic image data.
Priority Claims (1)
Number Date Country Kind
0525593 Dec 2005 GB national
CROSS-REFERENCE

The present application is a continuation application of U.S. patent application Ser. No. 16/376,918, entitled “Data Collection, Processing and Storage Systems for X-Ray Tomographic Images” and filed on Apr. 5, 2019, which is a continuation application of U.S. patent application Ser. No. 14/588,732, of the same title, filed on Jan. 2, 2015, and issued on May 21, 2019 as U.S. Pat. No. 10,295,483, which is a continuation application of U.S. patent application Ser. No. 13/370,941, of the same title, filed on Feb. 10, 2012, and issued on Feb. 17, 2015 as U.S. Pat. No. 8,958,526, which is a continuation application of U.S. patent application Ser. No. 12/142,005, entitled “X-Ray Tomography Inspection Systems”, filed on Jun. 19, 2008, and issued on Mar. 13, 2012 as U.S. Pat. No. 8,135,110, which is a continuation application of U.S. patent application Ser. No. 12/097,422, of the same title, filed on Jun. 13, 2008, and issued on Jan. 25, 2011 as U.S. Pat. No. 7,876,879, which is a National Stage application of PCT/GB2006/004684, filed on Dec. 15, 2006, which further claims priority from Great Britain Patent Application Number 0525593.0, filed on Dec. 16, 2005. All of the above referenced applications are incorporated herein by reference in their entirety.

US Referenced Citations (946)
Number Name Date Kind
768538 McElroy Aug 1904 A
2005180 Cronin Jun 1935 A
2006291 Barrows Jun 1935 A
2007003 Rosen Jul 1935 A
2009060 Hiers Jul 1935 A
2010020 Holzwarth Aug 1935 A
2010278 Snyder Aug 1935 A
2101143 Laidig Dec 1937 A
2299251 Perbal Oct 1942 A
2333525 Cox Nov 1943 A
2831123 Daly Apr 1958 A
2842694 Hosemann Jul 1958 A
2952790 Steen Sep 1960 A
2999935 Foster Sep 1961 A
3138729 Henke Jun 1964 A
3143651 Giacconi Aug 1964 A
3239706 Farrell Mar 1966 A
3610994 Sheldon Oct 1971 A
3707672 Miller Dec 1972 A
3713156 Pothier Jan 1973 A
3766387 Heffan Oct 1973 A
3768645 Conway Oct 1973 A
3780291 Stein Dec 1973 A
3784837 Holmstrom Jan 1974 A
3790785 Paolini Feb 1974 A
3790799 Stein Feb 1974 A
3848130 Macovski Nov 1974 A
3854049 Mistretta Dec 1974 A
3867637 Braun Feb 1975 A
RE28544 Stein Sep 1975 E
3965358 Macovski Jun 1976 A
3980889 Haas Sep 1976 A
4031401 Jacob Jun 1977 A
4031545 Stein Jun 1977 A
4045672 Watanabe Aug 1977 A
4047035 Dennhoven Sep 1977 A
4057725 Wagner Nov 1977 A
4064411 Iwasaki Dec 1977 A
4105922 Lambert Aug 1978 A
4122783 Pretini Oct 1978 A
4139771 Dennhoven Feb 1979 A
4158770 Davis, Jr. Jun 1979 A
4165472 Wittry Aug 1979 A
4171254 Koenecke Oct 1979 A
4185205 Ballas Jan 1980 A
4200800 Swift Apr 1980 A
4210811 Dennhoven Jul 1980 A
4216499 Dennhoven Aug 1980 A
4228353 Johnson Oct 1980 A
4228357 Annis Oct 1980 A
4238706 Hayasaka Dec 1980 A
4241404 Lux Dec 1980 A
4242583 Annis Dec 1980 A
4245158 Burstein Jan 1981 A
4259721 Kuznia Mar 1981 A
4260898 Annis Apr 1981 A
4266425 Allport May 1981 A
4274005 Yamamura Jun 1981 A
4297580 Juner Oct 1981 A
4303860 Bjorkholm Dec 1981 A
4309637 Fetter Jan 1982 A
4340816 Schott Jul 1982 A
4342914 Bjorkholm Aug 1982 A
4344011 Hayashi Aug 1982 A
4352021 Boyd Sep 1982 A
4352196 Gabbay Sep 1982 A
4366382 Kotowski Dec 1982 A
4366576 Annis Dec 1982 A
4375695 Harding Mar 1983 A
4384209 Wagner May 1983 A
4389729 Stein Jun 1983 A
4399403 Strandberg, Jr. Aug 1983 A
4405876 Iversen Sep 1983 A
4414682 Annis Nov 1983 A
4420382 Riedl Dec 1983 A
4422177 Mastronardi Dec 1983 A
4430568 Yoshida Feb 1984 A
4461020 Huebner Jul 1984 A
4468802 Friedel Aug 1984 A
4471343 Lemelson Sep 1984 A
4472822 Swift Sep 1984 A
4511799 Bjorkholm Apr 1985 A
4531226 Peschmann Jul 1985 A
4566113 Doenges Jan 1986 A
4571491 Vinegar Feb 1986 A
4593355 Chase Jun 1986 A
4599740 Cable Jul 1986 A
4622687 Whitaker Nov 1986 A
4622688 Diemer Nov 1986 A
4625324 Blaskis Nov 1986 A
4641330 Herwig Feb 1987 A
4670895 Penato Jun 1987 A
4672649 Rutt Jun 1987 A
4675890 Plessis Jun 1987 A
4677651 Hartl Jun 1987 A
4691332 Burstein Sep 1987 A
4719645 Yamabe Jan 1988 A
4736400 Koller Apr 1988 A
4736401 Donges Apr 1988 A
4754469 Harding Jun 1988 A
4763345 Barbaric Aug 1988 A
4768214 Bjorkholm Aug 1988 A
4788704 Donges Nov 1988 A
4788706 Jacobson Nov 1988 A
4789930 Sones Dec 1988 A
4799247 Annis Jan 1989 A
4809312 Annis Feb 1989 A
4825454 Annis Apr 1989 A
RE32961 Wagner Jun 1989 E
4845731 Vidmar Jul 1989 A
4845769 Burstein Jul 1989 A
4852131 Armistead Jul 1989 A
4866745 Akai Sep 1989 A
4868856 Frith Sep 1989 A
4884289 Glockmann Nov 1989 A
4887604 Shefer Dec 1989 A
4893015 Kubierschky Jan 1990 A
4894775 Kritchman Jan 1990 A
4899283 Annis Feb 1990 A
4928296 Kadambi May 1990 A
4945562 Staub Jul 1990 A
4956856 Harding Sep 1990 A
4958363 Nelson Sep 1990 A
4963746 Morgan Oct 1990 A
4975968 Yukl Dec 1990 A
4979202 Siczek Dec 1990 A
4987584 Doenges Jan 1991 A
4991189 Boomgaarden Feb 1991 A
4991194 Laurent Feb 1991 A
5007072 Jenkins Apr 1991 A
5008911 Harding Apr 1991 A
5018181 Iversen May 1991 A
5022062 Annis Jun 1991 A
5033106 Kita Jul 1991 A
5056124 Kakimoto Oct 1991 A
5056127 Iversen Oct 1991 A
5065418 Bermbach Nov 1991 A
5068882 Eberhard Nov 1991 A
5073910 Eberhard Dec 1991 A
5081456 Michiguchi Jan 1992 A
5091924 Bermbach Feb 1992 A
5091927 Golitzer Feb 1992 A
5098640 Gozani Mar 1992 A
5105452 McInerney Apr 1992 A
5127030 Annis Jun 1992 A
5138308 Clerc Aug 1992 A
5144191 Jones Sep 1992 A
5155365 Cann Oct 1992 A
5159234 Wegmann Oct 1992 A
5172401 Asari Dec 1992 A
5179581 Annis Jan 1993 A
5181234 Smith Jan 1993 A
5182764 Peschmann Jan 1993 A
5191600 Vincent Mar 1993 A
5195112 Vincent Mar 1993 A
5224144 Annis Jun 1993 A
5227800 Huguenin Jul 1993 A
5237598 Albert Aug 1993 A
5247556 Eckert Sep 1993 A
5247561 Kotowski Sep 1993 A
5253283 Annis Oct 1993 A
5259014 Brettschneider Nov 1993 A
5263075 McGann Nov 1993 A
5265144 Harding Nov 1993 A
5268955 Burke Dec 1993 A
5272627 Maschhoff Dec 1993 A
5305363 Burke Apr 1994 A
5313511 Annis May 1994 A
5319547 Krug Jun 1994 A
5329180 Popli Jul 1994 A
5339080 Steinway Aug 1994 A
5345240 Frazier Sep 1994 A
5365567 Ohtsuchi Nov 1994 A
5367552 Peschmann Nov 1994 A
5375156 Kuo-Petravic Dec 1994 A
5379334 Zimmer Jan 1995 A
5410156 Miller Apr 1995 A
5412702 Sata May 1995 A
5414622 Walters May 1995 A
5420905 Bertozzi May 1995 A
5428657 Papanicolopoulos Jun 1995 A
5467377 Dawson Nov 1995 A
5481584 Tang Jan 1996 A
5490196 Rudich Feb 1996 A
5490218 Krug Feb 1996 A
5493596 Annis Feb 1996 A
5511104 Mueller Apr 1996 A
5515414 D Achard Van Enschut May 1996 A
5524133 Neale Jun 1996 A
5541975 Anderson Jul 1996 A
5552705 Keller Sep 1996 A
5557108 Tumer Sep 1996 A
5557283 Sheen Sep 1996 A
5568829 Crawford Oct 1996 A
5570403 Yamazaki Oct 1996 A
5596621 Schwarz Jan 1997 A
5600303 Husseiny Feb 1997 A
5600700 Krug Feb 1997 A
5604778 Polacin Feb 1997 A
5606167 Miller Feb 1997 A
5616926 Shinada Apr 1997 A
5633906 Hell May 1997 A
5633907 Gravelle May 1997 A
5638420 Armistead Jun 1997 A
5642393 Krug Jun 1997 A
5642394 Rothschild Jun 1997 A
5648997 Chao Jul 1997 A
5651047 Moorman Jul 1997 A
5654995 Flohr Aug 1997 A
5661774 Gordon Aug 1997 A
5666393 Annis Sep 1997 A
5680432 Voss Oct 1997 A
5687210 Maitrejean Nov 1997 A
5689239 Turner Nov 1997 A
5689541 Schardt Nov 1997 A
5692028 Geus Nov 1997 A
5712889 Lanzara Jan 1998 A
5712926 Eberhard Jan 1998 A
5745543 De Bokx Apr 1998 A
5751837 Watanabe May 1998 A
5764683 Swift Jun 1998 A
5768334 Maitrejean Jun 1998 A
5787145 Geus Jul 1998 A
5796802 Gordon Aug 1998 A
5798972 Lao Aug 1998 A
5805660 Perion Sep 1998 A
5812630 Blaffert Sep 1998 A
5818897 Gordon Oct 1998 A
5838758 Krug Nov 1998 A
5838759 Armistead Nov 1998 A
5841831 Hell Nov 1998 A
5841832 Mazess Nov 1998 A
5859891 Hibbard Jan 1999 A
5864146 Karellas Jan 1999 A
5879807 Inoue Mar 1999 A
5881122 Crawford Mar 1999 A
5887047 Bailey Mar 1999 A
5889833 Silver Mar 1999 A
5901198 Crawford May 1999 A
5903623 Swift May 1999 A
5905806 Eberhard May 1999 A
5907593 Hsieh May 1999 A
5909477 Crawford Jun 1999 A
5910973 Grodzins Jun 1999 A
5930326 Rothschild Jul 1999 A
5940468 Huang Aug 1999 A
5943388 Tuemer Aug 1999 A
5966422 Dafni Oct 1999 A
5974111 Krug Oct 1999 A
5982843 Bailey Nov 1999 A
5987097 Salasoo Nov 1999 A
6014419 Hu Jan 2000 A
6018562 Willson Jan 2000 A
6021174 Campbell Feb 2000 A
6026135 McFee Feb 2000 A
6026143 Simanovsky Feb 2000 A
6026171 Hiraoglu Feb 2000 A
6031890 Bermbach Feb 2000 A
6035014 Hiraoglu Mar 2000 A
6037597 Karavolos Mar 2000 A
6054712 Komardin Apr 2000 A
6058158 Eiler May 2000 A
6067344 Grodzins May 2000 A
6067366 Simanovsky May 2000 A
6075836 Ning Jun 2000 A
6075871 Simanovsky Jun 2000 A
6076400 Bechwati Jun 2000 A
6078642 Simanovsky Jun 2000 A
6081580 Grodzins Jun 2000 A
6088423 Krug Jul 2000 A
6088426 Miller Jul 2000 A
6091795 Schafer Jul 2000 A
6094472 Smith Jul 2000 A
6108396 Bechwati Aug 2000 A
6108575 Besson Aug 2000 A
6111974 Hiraoglu Aug 2000 A
6118850 Mayo Sep 2000 A
6118852 Rogers Sep 2000 A
6122343 Pidcock Sep 2000 A
6125167 Morgan Sep 2000 A
6128365 Bechwati Oct 2000 A
6130502 Kobayashi Oct 2000 A
6149592 Yanof Nov 2000 A
6151381 Grodzins Nov 2000 A
6163591 Benjamin Dec 2000 A
6181765 Sribar Jan 2001 B1
6183139 Solomon Feb 2001 B1
6184841 Shober Feb 2001 B1
6185272 Hiraoglu Feb 2001 B1
6188743 Tybinkowski Feb 2001 B1
6188745 Gordon Feb 2001 B1
6188747 Geus Feb 2001 B1
6192101 Grodzins Feb 2001 B1
6192104 Adams Feb 2001 B1
6195413 Geus Feb 2001 B1
6195444 Simanovsky Feb 2001 B1
6198795 Naumann Mar 2001 B1
6216540 Nelson Apr 2001 B1
6218943 Ellenbogen Apr 2001 B1
6229870 Morgan May 2001 B1
6236709 Perry May 2001 B1
6240157 Danielsson May 2001 B1
6249567 Rothschild Jun 2001 B1
6252929 Swift Jun 2001 B1
6252932 Arakawa Jun 2001 B1
6256369 Lai Jul 2001 B1
6256404 Gordon Jul 2001 B1
6269142 Smith Jul 2001 B1
6272230 Hiraoglu Aug 2001 B1
6278115 Annis Aug 2001 B1
6282260 Grodzins Aug 2001 B1
6288676 Maloney Sep 2001 B1
6292533 Swift Sep 2001 B1
6298110 Ning Oct 2001 B1
6301326 Bjorkholm Oct 2001 B2
6304629 Conway Oct 2001 B1
6317509 Simanovsky Nov 2001 B1
6320933 Grodzins Nov 2001 B1
6324243 Edic Nov 2001 B1
6324249 Fazzio Nov 2001 B1
6332015 Honda Dec 2001 B1
6341154 Besson Jan 2002 B1
6342696 Chadwick Jan 2002 B1
6345113 Crawford Feb 2002 B1
6347132 Annis Feb 2002 B1
6356620 Rothschild Mar 2002 B1
6359582 MacAleese Mar 2002 B1
6385292 Dunham May 2002 B1
6404230 Cairns Jun 2002 B1
6417797 Cousins Jul 2002 B1
6418189 Schafer Jul 2002 B1
6421420 Grodzins Jul 2002 B1
6424695 Grodzins Jul 2002 B1
6429578 Danielsson Aug 2002 B1
6430255 Fenkart Aug 2002 B2
6430260 Snyder Aug 2002 B1
6434219 Rothschild Aug 2002 B1
6435715 Betz Aug 2002 B1
6438201 Mazess Aug 2002 B1
6442233 Grodzins Aug 2002 B1
6445765 Frank Sep 2002 B1
6449331 Nutt Sep 2002 B1
6449337 Honda Sep 2002 B1
6453003 Springer Sep 2002 B1
6453007 Adams Sep 2002 B2
6456093 Merkel Sep 2002 B1
6456684 Mun Sep 2002 B1
6459755 Li Oct 2002 B1
6459761 Grodzins Oct 2002 B1
6459764 Chalmers Oct 2002 B1
6469624 Whan Oct 2002 B1
6470065 Lauther Oct 2002 B1
6473487 Le Oct 2002 B1
RE37899 Grodzins Nov 2002 E
6480141 Toth Nov 2002 B1
6480571 Andrews Nov 2002 B1
6483894 Hartick Nov 2002 B2
6501414 Arndt Dec 2002 B2
6507025 Verbinski Jan 2003 B1
6532276 Hartick Mar 2003 B1
6542574 Grodzins Apr 2003 B2
6542578 Ries Apr 2003 B2
6542580 Carver Apr 2003 B1
6546072 Chalmers Apr 2003 B1
6552346 Verbinski Apr 2003 B2
6553096 Zhou Apr 2003 B1
6556653 Hussein Apr 2003 B2
6563903 Kang May 2003 B2
6563906 Hussein May 2003 B2
6580778 Meder Jun 2003 B2
6580780 Miller Jun 2003 B1
6584170 Aust Jun 2003 B2
6590956 Fenkart Jul 2003 B2
6597760 Beneke Jul 2003 B2
6606516 Levine Aug 2003 B2
6618466 Ning Sep 2003 B1
6621888 Grodzins Sep 2003 B2
6624425 Nisius Sep 2003 B2
6628745 Annis Sep 2003 B1
6636581 Sorenson Oct 2003 B2
6642513 Jenkins Nov 2003 B1
6647091 Fenkart Nov 2003 B2
6647094 Harding Nov 2003 B2
6647095 Hsieh Nov 2003 B2
6650276 Lawless Nov 2003 B2
6653588 Gillard-Hickman Nov 2003 B1
6654440 Hsieh Nov 2003 B1
6658087 Chalmers Dec 2003 B2
6661866 Limkeman Dec 2003 B1
6663280 Doenges Dec 2003 B2
6665373 Kotowski Dec 2003 B1
6665433 Roder Dec 2003 B2
6674838 Barrett Jan 2004 B1
6687333 Carroll Feb 2004 B2
6690766 Kresse Feb 2004 B2
6707879 McClelland Mar 2004 B2
6715533 Kresse Apr 2004 B2
6721387 Naidu Apr 2004 B1
6735271 Rand May 2004 B1
6737652 Lanza May 2004 B2
6748043 Dobbs Jun 2004 B1
6751293 Barrett Jun 2004 B1
6754298 Fessler Jun 2004 B2
6760407 Price Jul 2004 B2
6763635 Lowman Jul 2004 B1
6768317 Moeller Jul 2004 B2
6770884 Bryman Aug 2004 B2
6775348 Hoffman Aug 2004 B2
6785357 Bernardi Aug 2004 B2
6785359 Lemaitre Aug 2004 B2
6788761 Bijjani Sep 2004 B2
6798863 Sato Sep 2004 B2
6807248 Mihara Oct 2004 B2
6812426 Kotowski Nov 2004 B1
6813374 Karimi Nov 2004 B1
6815670 Jenkins Nov 2004 B2
6816571 Bijjani Nov 2004 B2
6819742 Miller Nov 2004 B1
6827265 Knowles Dec 2004 B2
6830185 Tsikos Dec 2004 B2
6831590 Steinway Dec 2004 B1
6837422 Meder Jan 2005 B1
6837432 Tsikos Jan 2005 B2
6839403 Kotowski Jan 2005 B1
6840122 Jenkins Jan 2005 B1
6843599 Le Jan 2005 B2
6856271 Hausner Feb 2005 B1
6856667 Ellenbogen Feb 2005 B2
6859514 Hoffman Feb 2005 B2
6876322 Keller Apr 2005 B2
6891381 Bailey May 2005 B2
6894636 Anderton May 2005 B2
6901135 Fox May 2005 B2
6906329 Bryman Jun 2005 B2
6907101 Hoffman Jun 2005 B2
6920196 Ueno Jul 2005 B2
6920197 Kang Jul 2005 B2
6922455 Jurczyk Jul 2005 B2
6922460 Skatter Jul 2005 B2
6922461 Kang Jul 2005 B2
6928141 Carver Aug 2005 B2
6933504 Hoffman Aug 2005 B2
6934354 Hoffman Aug 2005 B2
6940071 Ramsden Sep 2005 B2
6944264 Bijjani Sep 2005 B2
6947517 Hoffman Sep 2005 B2
6950492 Besson Sep 2005 B2
6950493 Besson Sep 2005 B2
6952163 Huey Oct 2005 B2
6953935 Hoffman Oct 2005 B1
6957913 Renkart Oct 2005 B2
6962289 Vatan Nov 2005 B2
6968030 Hoffman Nov 2005 B2
6968034 Ellenbogen Nov 2005 B2
6971577 Tsikos Dec 2005 B2
6973158 Besson Dec 2005 B2
6975698 Katcha Dec 2005 B2
6975703 Wilson Dec 2005 B2
6978936 Tsikos Dec 2005 B2
6980627 Qiu Dec 2005 B2
6990171 Toth Jan 2006 B2
6990172 Toth Jan 2006 B2
6991371 Georgeson Jan 2006 B2
6993115 McGuire Jan 2006 B2
6996209 Marek Feb 2006 B2
7010083 Hoffman Mar 2006 B2
7010094 Grodzins Mar 2006 B2
7012256 Roos Mar 2006 B1
7012989 Holland Mar 2006 B2
7016459 Ellenbogen Mar 2006 B2
7020232 Rand Mar 2006 B2
7020241 Beneke Mar 2006 B2
7020242 Ellenbogen Mar 2006 B2
7023950 Annis Apr 2006 B1
7023956 Heaton Apr 2006 B2
7023957 Bijjani Apr 2006 B2
7027553 Dunham Apr 2006 B2
7027554 Gaultier Apr 2006 B2
7031430 Kaucic, Jr. Apr 2006 B2
7031434 Saunders Apr 2006 B1
7034313 Hoffman Apr 2006 B2
7039154 Ellenbogen May 2006 B1
7039159 Muenchau May 2006 B2
7045787 Verbinski May 2006 B1
7046756 Hoffman May 2006 B2
7046761 Ellenbogen May 2006 B2
7050529 Hoffman May 2006 B2
7050536 Fenkart May 2006 B1
7050540 Wilkins May 2006 B2
7054408 Jiang May 2006 B2
7062009 Karimi Jun 2006 B2
7062011 Tybinkowski Jun 2006 B1
7062074 Beneke Jun 2006 B1
7064334 Hoffman Jun 2006 B2
7065175 Green Jun 2006 B2
7065179 Block Jun 2006 B2
7068749 Kollegal Jun 2006 B2
7068750 Toth Jun 2006 B2
7068751 Toth Jun 2006 B2
7072434 Tybinkowski Jul 2006 B1
7076029 Toth Jul 2006 B2
7078699 Seppi Jul 2006 B2
7079624 Miller Jul 2006 B1
7081628 Granfors Jul 2006 B2
7084404 Hoffman Aug 2006 B2
7087902 Wang Aug 2006 B2
7088799 Hoffman Aug 2006 B2
7090133 Zhu Aug 2006 B2
7092481 Hoffman Aug 2006 B2
7092485 Kravis Aug 2006 B2
7099434 Adams Aug 2006 B2
7103137 Seppi Sep 2006 B2
7106830 Rosner Sep 2006 B2
7110488 Katcha Sep 2006 B2
7110493 Kotowski Sep 2006 B1
7112797 Hoge Sep 2006 B2
7116749 Besson Oct 2006 B2
7116751 Ellenbogen Oct 2006 B2
7119553 Yang Oct 2006 B2
7120222 Hoffman Oct 2006 B2
7123681 Ellenbogen Oct 2006 B2
7127027 Hoffman Oct 2006 B2
7130374 Jacobs Oct 2006 B1
RE39396 Swift Nov 2006 E
7133491 Bernardi Nov 2006 B2
7136450 Ying Nov 2006 B2
7136451 Naidu Nov 2006 B2
7139367 Le Nov 2006 B1
7139406 McClelland Nov 2006 B2
7142629 Edic Nov 2006 B2
7149278 Arenson Dec 2006 B2
7149339 Veneruso Dec 2006 B2
7155812 Peterson Jan 2007 B1
7158611 Heismann Jan 2007 B2
7164747 Ellenbogen Jan 2007 B2
7164750 Nabors Jan 2007 B2
7166458 Ballerstadt Jan 2007 B2
7167539 Hoffman Jan 2007 B1
7173998 Hoffman Feb 2007 B2
7177387 Yasunaga Feb 2007 B2
7177391 Chapin Feb 2007 B2
7183906 Zanovitch Feb 2007 B2
7184520 Sano Feb 2007 B1
7184814 Lang Feb 2007 B2
7187756 Gohno Mar 2007 B2
7190757 Ying Mar 2007 B2
7192031 Dunham Mar 2007 B2
7197113 Katcha Mar 2007 B1
7197116 Dunham Mar 2007 B2
7197172 Naidu Mar 2007 B1
7203269 Huber Apr 2007 B2
7203271 Benz Apr 2007 B2
7203282 Brauss Apr 2007 B2
7203629 Oezis Apr 2007 B2
7206379 Lemaitre Apr 2007 B2
7207713 Lowman Apr 2007 B2
7215731 Basu May 2007 B1
7215738 Muenchau May 2007 B2
7218700 Huber May 2007 B2
7218704 Adams May 2007 B1
7224763 Naidu May 2007 B2
7224765 Ellenbogen May 2007 B2
7224766 Jiang May 2007 B2
7224769 Turner May 2007 B2
7233640 Ikhlef Jun 2007 B2
7233644 Bendahan Jun 2007 B1
7236564 Hopkins Jun 2007 B2
7238945 Hoffman Jul 2007 B2
7247856 Hoge Jul 2007 B2
7248673 Miller Jul 2007 B2
7251310 Smith Jul 2007 B2
7253727 Jenkins Aug 2007 B2
7260170 Arenson Aug 2007 B2
7260171 Arenson Aug 2007 B1
7260172 Arenson Aug 2007 B2
7260173 Wakayama Aug 2007 B2
7260174 Hoffman Aug 2007 B2
7260182 Toth Aug 2007 B2
7261466 Bhatt Aug 2007 B2
7263160 Schlomka Aug 2007 B2
7266180 Saunders Sep 2007 B1
7272429 Walker Sep 2007 B2
7274767 Clayton Sep 2007 B2
7277577 Ying Oct 2007 B2
7279120 Cheng Oct 2007 B2
7280631 De Man Oct 2007 B2
7282727 Retsky Oct 2007 B2
7283604 De Man Oct 2007 B2
7283609 Possin Oct 2007 B2
7295019 Yang Nov 2007 B2
7295651 Delgado Nov 2007 B2
7295691 Uppaluri Nov 2007 B2
7298812 Tkaczyk Nov 2007 B2
7302083 Larson Nov 2007 B2
7308073 Tkaczyk Dec 2007 B2
7308074 Jiang Dec 2007 B2
7308077 Bijjani Dec 2007 B2
7317195 Eikman Jan 2008 B2
7317390 Huey Jan 2008 B2
7319737 Singh Jan 2008 B2
7322745 Agrawal Jan 2008 B2
7324625 Eilbert Jan 2008 B2
7327853 Ying Feb 2008 B2
7330527 Hoffman Feb 2008 B2
7330535 Arenson Feb 2008 B2
7333587 De Man Feb 2008 B2
7333588 Mistretta Feb 2008 B2
7333589 Ellenbogen Feb 2008 B2
7335887 Verbinski Feb 2008 B1
7336769 Arenson Feb 2008 B2
7340525 Bhatia Mar 2008 B1
7349525 Morton Mar 2008 B2
7354197 Bhatt Apr 2008 B2
7356174 Leue Apr 2008 B2
7366280 Lounsberry Apr 2008 B2
7366282 Peschmann Apr 2008 B2
7369640 Seppi May 2008 B2
7369643 Kotowski May 2008 B2
7372934 De Man May 2008 B2
7376218 Chapin May 2008 B2
7400701 Cason Jul 2008 B1
7412026 Liu Aug 2008 B2
7417440 Peschmann Aug 2008 B2
7418073 Schlomka Aug 2008 B2
7426260 Cantu Sep 2008 B2
7440543 Morton Oct 2008 B2
7466799 Miller Dec 2008 B2
7474786 Naidu Jan 2009 B2
7483510 Carver Jan 2009 B2
7486760 Harding Feb 2009 B2
7486768 Allman Feb 2009 B2
7486769 Brondo, Jr. Feb 2009 B2
7490984 Bhatt Feb 2009 B2
7492855 Hopkins Feb 2009 B2
7505563 Morton Mar 2009 B2
7508916 Frontera Mar 2009 B2
7510324 Bhatt Mar 2009 B2
7512215 Morton Mar 2009 B2
7539337 Simanovsky May 2009 B2
7551714 Rothschild Jun 2009 B2
7551718 Rothschild Jun 2009 B2
7555099 Rothschild Jun 2009 B2
7564939 Morton Jul 2009 B2
7565939 Ando Jul 2009 B2
7579845 Peschmann Aug 2009 B2
7590215 Schlomka Sep 2009 B2
7593506 Cason Sep 2009 B2
7596275 Richardson Sep 2009 B1
7636638 Russ Dec 2009 B2
7643866 Heismann Jan 2010 B2
7649981 Seppi Jan 2010 B2
7664230 Morton Feb 2010 B2
7684538 Morton Mar 2010 B2
7697665 Yonezawa Apr 2010 B2
7724868 Morton May 2010 B2
7728397 Gorrell Jun 2010 B2
7734066 Delia Jun 2010 B2
7738632 Popescu Jun 2010 B2
7769132 Hurd Aug 2010 B1
7778382 Hoffman Aug 2010 B2
7796795 Uppaluri Sep 2010 B2
7801348 Ying Sep 2010 B2
7835495 Harding Nov 2010 B2
7856081 Peschmann Dec 2010 B2
7864920 Rothschild Jan 2011 B2
7876879 Morton Jan 2011 B2
7885372 Edic Feb 2011 B2
7903789 Morton Mar 2011 B2
7924979 Rothschild Apr 2011 B2
7929663 Morton Apr 2011 B2
7949101 Morton May 2011 B2
7970096 Pavlovich Jun 2011 B2
7978816 Matsuura Jul 2011 B2
7995707 Rothschild Aug 2011 B2
8039812 Crocker Oct 2011 B1
8085897 Morton Dec 2011 B2
8094784 Morton Jan 2012 B2
8111803 Edic Feb 2012 B2
8135110 Morton Mar 2012 B2
8138770 Peschmann Mar 2012 B2
8204173 Betcke Jun 2012 B2
8223919 Morton Jul 2012 B2
8243876 Morton Aug 2012 B2
8311313 Gamble Nov 2012 B1
8331535 Morton Dec 2012 B2
8428217 Peschmann Apr 2013 B2
8451974 Morton May 2013 B2
8552722 Lionheart Oct 2013 B2
8559592 Betcke Oct 2013 B2
8625735 Morton Jan 2014 B2
8654924 Behling Feb 2014 B2
8804899 Morton Aug 2014 B2
8824637 Morton Sep 2014 B2
8837669 Morton Sep 2014 B2
8842808 Rothschild Sep 2014 B2
8885794 Morton Nov 2014 B2
8958526 Morton Feb 2015 B2
8971484 Beckmann Mar 2015 B2
9001973 Morton Apr 2015 B2
9020095 Morton Apr 2015 B2
9042511 Peschmann May 2015 B2
9046465 Thompson Jun 2015 B2
9048061 Morton Jun 2015 B2
9086497 Bendahan Jul 2015 B2
9093187 Johnson Jul 2015 B1
9093245 Morton Jul 2015 B2
9113839 Morton Aug 2015 B2
9158030 Morton Oct 2015 B2
9183647 Morton Nov 2015 B2
9208988 Morton Dec 2015 B2
9263225 Morton Feb 2016 B2
9286686 Lang Mar 2016 B2
9420677 Morton Aug 2016 B2
9442082 Morton Sep 2016 B2
9442213 Bendahan Sep 2016 B2
9562866 Morton Feb 2017 B2
9576766 Morton Feb 2017 B2
9606259 Morton Mar 2017 B2
9618648 Morton Apr 2017 B2
9638646 Morton May 2017 B2
9675306 Morton Jun 2017 B2
9714920 Lionheart Jul 2017 B2
9726619 Thompson Aug 2017 B2
9747705 Morton Aug 2017 B2
9915752 Peschmann Mar 2018 B2
10107783 Lionheart Oct 2018 B2
10175381 Morton Jan 2019 B2
10295483 Morton May 2019 B2
10591424 Morton Mar 2020 B2
20010022346 Katagami Sep 2001 A1
20010022830 Sommer Sep 2001 A1
20010033635 Kuwabara Oct 2001 A1
20010050972 Yamada Dec 2001 A1
20020008655 Haj-Yousef Jan 2002 A1
20020031202 Callerame Mar 2002 A1
20020082492 Grzeszczuk Jun 2002 A1
20020085674 Price Jul 2002 A1
20020094064 Zhou Jul 2002 A1
20020094117 Funahashi Jul 2002 A1
20020097836 Grodzins Jul 2002 A1
20020101958 Bertsche Aug 2002 A1
20020126798 Harris Sep 2002 A1
20020140336 Stoner Oct 2002 A1
20020176531 McClelland Nov 2002 A1
20020177770 Lang Nov 2002 A1
20030009202 Levine Jan 2003 A1
20030021377 Turner Jan 2003 A1
20030023592 Modica Jan 2003 A1
20030031352 Nelson Feb 2003 A1
20030043957 Pelc Mar 2003 A1
20030048868 Bailey Mar 2003 A1
20030053597 Flohr Mar 2003 A1
20030072407 Mihara Apr 2003 A1
20030076921 Mihara Apr 2003 A1
20030076924 Mario Apr 2003 A1
20030081720 Swift May 2003 A1
20030085163 Chan May 2003 A1
20030091148 Bittner May 2003 A1
20030108155 Wilkins Jun 2003 A1
20030179126 Jablonski Sep 2003 A1
20030190011 Beneke Oct 2003 A1
20030215120 Uppaluri Nov 2003 A1
20030216644 Hall Nov 2003 A1
20040016271 Shah Jan 2004 A1
20040017224 Tumer Jan 2004 A1
20040017887 Le Jan 2004 A1
20040017888 Seppi Jan 2004 A1
20040021623 Nicolas Feb 2004 A1
20040022292 Morton Feb 2004 A1
20040057554 Bjorkholm Mar 2004 A1
20040066879 Machida Apr 2004 A1
20040077943 Meaney Apr 2004 A1
20040081270 Heuscher Apr 2004 A1
20040094064 Taguchi May 2004 A1
20040094707 Jenkins May 2004 A1
20040096030 Banchieri May 2004 A1
20040101098 Bijjani May 2004 A1
20040109532 Ford Jun 2004 A1
20040120454 Ellenbogen Jun 2004 A1
20040141584 Bernardi Jul 2004 A1
20040202282 Miller Oct 2004 A1
20040213378 Zhou Oct 2004 A1
20040213379 Bittl Oct 2004 A1
20040223585 Heismann Nov 2004 A1
20040232054 Brown Nov 2004 A1
20040234023 Kollegal Nov 2004 A1
20040245449 Nakashige Dec 2004 A1
20040252807 Skatter Dec 2004 A1
20040258198 Carver Dec 2004 A1
20040258305 Burnham Dec 2004 A1
20050002492 Rother Jan 2005 A1
20050008073 Techmer Jan 2005 A1
20050031075 Hopkins Feb 2005 A1
20050053189 Gohno Mar 2005 A1
20050057354 Jenkins Mar 2005 A1
20050058242 Peschmann Mar 2005 A1
20050082491 Seppi Apr 2005 A1
20050084069 Du Apr 2005 A1
20050084073 Seppi Apr 2005 A1
20050089140 Mario Apr 2005 A1
20050100126 Mistretta May 2005 A1
20050100135 Lowman May 2005 A1
20050104603 Peschmann May 2005 A1
20050105665 Grodzins May 2005 A1
20050105682 Heumann May 2005 A1
20050111610 De Man May 2005 A1
20050111619 Bijjani May 2005 A1
20050117683 Mishin Jun 2005 A1
20050117700 Peschmann Jun 2005 A1
20050123092 Mistretta Jun 2005 A1
20050140603 Kim Jun 2005 A1
20050157842 Agrawal Jul 2005 A1
20050157925 Lorenz Jul 2005 A1
20050169422 Ellenbogen Aug 2005 A1
20050169423 Ellenbogen Aug 2005 A1
20050175151 Dunham Aug 2005 A1
20050180542 Leue Aug 2005 A1
20050190882 McGuire Sep 2005 A1
20050226364 Bernard De Man Oct 2005 A1
20050238232 Ying Oct 2005 A1
20050249416 Leue Nov 2005 A1
20050276377 Carol Dec 2005 A1
20050276382 Lesiak Dec 2005 A1
20050281390 Johnson Dec 2005 A1
20060002585 Larson Jan 2006 A1
20060008047 Zhou Jan 2006 A1
20060018428 Li Jan 2006 A1
20060050842 Wang Mar 2006 A1
20060056584 Allman Mar 2006 A1
20060098773 Peschmann May 2006 A1
20060109949 Tkaczyk May 2006 A1
20060109954 Gohno May 2006 A1
20060113163 Hu Jun 2006 A1
20060133571 Winsor Jun 2006 A1
20060134000 Heismann Jun 2006 A1
20060140341 Carver Jun 2006 A1
20060145771 Strange Jul 2006 A1
20060203961 Morton Sep 2006 A1
20060233295 Edic Oct 2006 A1
20060233297 Ishiyama Oct 2006 A1
20060256924 Morton Nov 2006 A1
20060273259 Li Dec 2006 A1
20060280286 Kaval Dec 2006 A1
20060291623 Smith Dec 2006 A1
20070003003 Seppi Jan 2007 A1
20070014471 Simanovsky Jan 2007 A1
20070014472 Ying Jan 2007 A1
20070025512 Gertsenshteyn Feb 2007 A1
20070031036 Naidu Feb 2007 A1
20070053495 Morton Mar 2007 A1
20070064873 Gabioud Mar 2007 A1
20070096030 Li May 2007 A1
20070110215 Hu May 2007 A1
20070122003 Dobkin May 2007 A1
20070133740 Kang Jun 2007 A1
20070172023 Morton Jul 2007 A1
20070172024 Morton Jul 2007 A1
20070183568 Kang Aug 2007 A1
20070183575 Lemaitre Aug 2007 A1
20070189597 Limer Aug 2007 A1
20070203430 Lang Aug 2007 A1
20070205367 Deman Sep 2007 A1
20070237288 Tkaczyk Oct 2007 A1
20070242802 Dafni Oct 2007 A1
20070263767 Brondo, Jr. Nov 2007 A1
20070269005 Chalmers Nov 2007 A1
20070297570 Kerpershoek Dec 2007 A1
20080019483 Andrews Jan 2008 A1
20080031507 Uppaluri Feb 2008 A1
20080043912 Harding Feb 2008 A1
20080043920 Liu Feb 2008 A1
20080056432 Pack Mar 2008 A1
20080056435 Basu Mar 2008 A1
20080056436 Pack Mar 2008 A1
20080056437 Pack Mar 2008 A1
20080056444 Skatter Mar 2008 A1
20080069420 Zhang Mar 2008 A1
20080112540 Rogers May 2008 A1
20080123803 De Man May 2008 A1
20080130974 Xu Jun 2008 A1
20080144774 Mortor Jun 2008 A1
20080198967 Connelly Aug 2008 A1
20080213803 Cowley Sep 2008 A1
20080237480 Robinson Oct 2008 A1
20080267355 Morton Oct 2008 A1
20080304622 Morton Dec 2008 A1
20090003514 Edic Jan 2009 A1
20090010386 Peschmann Jan 2009 A1
20090022264 Zhou Jan 2009 A1
20090034792 Kennison Feb 2009 A1
20090041186 Gray Feb 2009 A1
20090060135 Morton Mar 2009 A1
20090086898 Richardson Apr 2009 A1
20090097836 Tanaka Apr 2009 A1
20090110259 Yin Apr 2009 A1
20090147910 Edic Jun 2009 A1
20090159451 Tomantschger Jun 2009 A1
20090161816 De Man Jun 2009 A1
20090168958 Cozzini Jul 2009 A1
20090185660 Zou Jul 2009 A1
20090207967 Liu Aug 2009 A1
20090213989 Harding Aug 2009 A1
20090265386 March Oct 2009 A1
20090274277 Morton Nov 2009 A1
20090316855 Morton Dec 2009 A1
20100020920 Mertelmeier Jan 2010 A1
20100020934 Morton Jan 2010 A1
20100046716 Freudenberger Feb 2010 A1
20100098219 Vermilyea Apr 2010 A1
20100111265 Holm May 2010 A1
20100172476 Morton Jul 2010 A1
20100220835 Gibson Sep 2010 A1
20100246754 Morton Sep 2010 A1
20100284509 Oreper Nov 2010 A1
20100316192 Hauttmann Dec 2010 A1
20100329532 Masuda Dec 2010 A1
20110007876 Morton Jan 2011 A1
20110170757 Pan Jul 2011 A1
20110188725 Yu Aug 2011 A1
20110222662 Behling Sep 2011 A1
20110228899 Funk Sep 2011 A1
20110243382 Morton Oct 2011 A1
20110243413 Tkaczyk Oct 2011 A1
20110249788 Nueesch Oct 2011 A1
20120219116 Thompson Aug 2012 A1
20120230463 Morton Sep 2012 A1
20130156161 Andrews Jun 2013 A1
20130170611 Beckmann Jul 2013 A1
20130195253 Andrews Aug 2013 A1
20130251098 Morton Sep 2013 A1
20130264483 Abenaim Oct 2013 A1
20140023181 Noshi Jan 2014 A1
20140185754 Tang Jul 2014 A1
20140211916 Morton Jul 2014 A1
20140294147 Chen Oct 2014 A1
20140342631 Morton Nov 2014 A1
20150355117 Morton Dec 2015 A1
20150357148 Morton Dec 2015 A1
20160343533 Morton Nov 2016 A1
20170161922 Morton Jun 2017 A1
20180038988 Morton Feb 2018 A1
20180128754 Thompson May 2018 A1
20190178821 Morton Jun 2019 A1
20190353821 Morton Nov 2019 A1
20200103357 Morton Apr 2020 A1
20200200690 Morton Jun 2020 A1
Foreign Referenced Citations (345)
Number Date Country
392160 Feb 1991 AT
2003254124 Feb 2004 AU
2365045 Jun 2003 CA
85107860 Oct 1986 CN
1050769 Apr 1991 CN
1130498 Sep 1996 CN
1138743 Dec 1996 CN
1172952 Feb 1998 CN
1194718 Sep 1998 CN
1309768 Aug 2001 CN
1316827 Oct 2001 CN
1550215 Dec 2004 CN
1626039 Jun 2005 CN
1708256 Dec 2005 CN
1745296 Mar 2006 CN
1780585 May 2006 CN
1795527 Jun 2006 CN
100371689 Jul 2006 CN
1820705 Aug 2006 CN
1937961 Mar 2007 CN
101048802 Oct 2007 CN
201034948 Mar 2008 CN
101185577 May 2008 CN
101189534 May 2008 CN
101303317 Nov 2008 CN
101512379 Aug 2009 CN
101842052 Sep 2010 CN
2729353 Jan 1979 DE
3638378 May 1988 DE
3840398 Jun 1989 DE
4410757 Jan 1995 DE
4432205 Jan 1996 DE
4425691 Feb 1996 DE
4436688 Apr 1996 DE
19745998 Mar 1999 DE
10036210 Nov 2001 DE
10319547 Nov 2004 DE
10319549 Dec 2004 DE
102004056590 Jun 2005 DE
102005048389 Apr 2007 DE
0115125 Aug 1984 EP
0142249 May 1985 EP
0198276 Oct 1986 EP
0424912 May 1991 EP
0432568 Jun 1991 EP
0531993 Mar 1993 EP
0564292 Oct 1993 EP
0584871 Mar 1994 EP
0795919 Sep 1997 EP
0873511 Oct 1998 EP
0924742 Jun 1999 EP
0930046 Jul 1999 EP
1063538 Dec 2000 EP
1277439 Jan 2003 EP
1298055 Apr 2003 EP
1371970 Dec 2003 EP
1374776 Jan 2004 EP
1540318 Jun 2005 EP
1558142 Aug 2005 EP
1617764 Jan 2006 EP
1618368 Jan 2006 EP
1618584 Jan 2006 EP
1620875 Feb 2006 EP
1689640 Aug 2006 EP
1969356 Sep 2008 EP
2002789 Dec 2008 EP
2017605 Jan 2009 EP
1618585 Jun 2009 EP
2151681 Feb 2010 EP
1739413 May 2010 EP
1618584 Sep 2011 EP
2406809 Jan 2012 EP
2435955 Apr 2012 EP
2436013 Apr 2012 EP
2278606 Oct 2013 EP
2287882 Oct 2013 EP
2267750 Nov 2013 EP
2678668 Jan 2014 EP
1970700 Jul 2014 EP
2854644 Apr 2015 EP
3267361 Jan 2018 EP
3282393 Feb 2018 EP
1618353 Feb 2019 EP
2328280 May 1977 FR
2675629 Oct 1992 FR
1149796 Apr 1969 GB
1272498 Apr 1972 GB
1497396 Jan 1978 GB
1526041 Sep 1978 GB
2015245 Sep 1979 GB
2089109 Jun 1982 GB
2133208 Jul 1984 GB
2212903 Aug 1989 GB
2212975 Aug 1989 GB
2244900 Dec 1991 GB
2329817 Mar 1995 GB
2285506 Jul 1995 GB
2299251 Sep 1996 GB
2356453 May 2001 GB
2360405 Sep 2001 GB
2360405 Sep 2001 GB
2414072 Nov 2005 GB
2416655 Feb 2006 GB
2416944 Feb 2006 GB
2417821 Mar 2006 GB
2418529 Mar 2006 GB
2423687 Aug 2006 GB
2437777 Nov 2007 GB
2471421 Dec 2010 GB
50012990 Feb 1975 JP
50081080 Jul 1975 JP
S51055286 May 1976 JP
S51078696 Jul 1976 JP
S52050186 Apr 1977 JP
S52124890 Oct 1977 JP
S5427793 Mar 1979 JP
S5493993 Jul 1979 JP
S5046408 Apr 1980 JP
56086448 Jul 1981 JP
S56167464 Dec 1981 JP
S5717524 Jan 1982 JP
S57110854 Jul 1982 JP
570175247 Oct 1982 JP
S57175247 Oct 1982 JP
58212045 Dec 1983 JP
590016254 Jan 1984 JP
S591625 Jan 1984 JP
S5916254 Jan 1984 JP
59075549 Apr 1984 JP
S5975549 Apr 1984 JP
59174744 Oct 1984 JP
600015546 Jan 1985 JP
S601554 Jan 1985 JP
600021440 Feb 1985 JP
S6038957 Feb 1985 JP
S60021440 Feb 1985 JP
60073442 Apr 1985 JP
S60181851 Dec 1985 JP
S61028039 Feb 1986 JP
61107642 May 1986 JP
S6104193 Oct 1986 JP
62044940 Feb 1987 JP
62064977 Mar 1987 JP
S62121773 Aug 1987 JP
63016535 Jan 1988 JP
S63150840 Jun 1988 JP
64034333 Feb 1989 JP
S6486938 Mar 1989 JP
1296544 Nov 1989 JP
03198975 Aug 1991 JP
H0479128 Mar 1992 JP
H04319237 Nov 1992 JP
05100037 Apr 1993 JP
H05135721 Jun 1993 JP
H05182617 Jul 1993 JP
05192327 Aug 1993 JP
H05060381 Sep 1993 JP
H05290768 Nov 1993 JP
5325851 Dec 1993 JP
H05325851 Dec 1993 JP
060038957 Feb 1994 JP
H0638957 Feb 1994 JP
H06133960 May 1994 JP
06162974 Jun 1994 JP
H06169911 Jun 1994 JP
H06261895 Sep 1994 JP
6296607 Oct 1994 JP
H07012756 Jan 1995 JP
H07057113 Mar 1995 JP
H07093525 Apr 1995 JP
H08178872 Jul 1996 JP
H08299322 Nov 1996 JP
H09171788 Jun 1997 JP
10005206 Jan 1998 JP
H10001209 Jan 1998 JP
10075944 Mar 1998 JP
1998075944 Mar 1998 JP
10506195 Jun 1998 JP
H10211196 Aug 1998 JP
H10272128 Oct 1998 JP
H11500229 Jan 1999 JP
11146871 Jun 1999 JP
H11230918 Aug 1999 JP
H11230918 Aug 1999 JP
11262486 Sep 1999 JP
H11273597 Oct 1999 JP
2000107173 Apr 2000 JP
2000175895 Jun 2000 JP
200113089 Jan 2001 JP
2001023557 Jan 2001 JP
2001502473 Feb 2001 JP
2001083171 Mar 2001 JP
2001176408 Jun 2001 JP
2001204723 Jul 2001 JP
2001233440 Aug 2001 JP
2001351551 Dec 2001 JP
2002039966 Feb 2002 JP
2002503816 Feb 2002 JP
2002162472 Jun 2002 JP
2002168805 Jun 2002 JP
2002195961 Jul 2002 JP
2002257751 Sep 2002 JP
2002535625 Oct 2002 JP
2002320610 Nov 2002 JP
2002343291 Nov 2002 JP
2002370814 Dec 2002 JP
2003092076 Mar 2003 JP
2003121392 Apr 2003 JP
2003126075 May 2003 JP
2003135442 May 2003 JP
2003257347 Sep 2003 JP
2004000605 Jan 2004 JP
2004079128 Mar 2004 JP
2004226253 Aug 2004 JP
2004233206 Aug 2004 JP
2004311245 Nov 2004 JP
2004347328 Dec 2004 JP
2004357724 Dec 2004 JP
2005013768 Jan 2005 JP
2005110722 Apr 2005 JP
2005177469 Jul 2005 JP
2005534009 Nov 2005 JP
2005534009 Nov 2005 JP
2006502386 Jan 2006 JP
2006071514 Mar 2006 JP
2006128137 May 2006 JP
2006167463 Jun 2006 JP
2006518039 Aug 2006 JP
2006320464 Nov 2006 JP
2006524809 Nov 2006 JP
2006351272 Dec 2006 JP
2007010455 Jan 2007 JP
2007500357 Jan 2007 JP
2007508561 Apr 2007 JP
2007265981 Oct 2007 JP
2007533993 Nov 2007 JP
2008113960 May 2008 JP
2008166059 Jul 2008 JP
2008178714 Aug 2008 JP
2008212840 Sep 2008 JP
2008268035 Nov 2008 JP
3147024 Dec 2008 JP
2009083632 Apr 2009 JP
2009519457 May 2009 JP
2010060572 Mar 2010 JP
100211196 Sep 2010 JP
1021026 Jan 2004 NL
1027596 Nov 2005 NL
1022236 Jun 1983 SU
9217771 Oct 1992 WO
1992017771 Oct 1992 WO
9528715 Oct 1995 WO
9718462 May 1997 WO
9718462 May 1997 WO
1997018462 May 1997 WO
1998002763 Jan 1998 WO
9941676 Aug 1999 WO
199950882 Oct 1999 WO
1999050882 Oct 1999 WO
9960387 Nov 1999 WO
0231857 Apr 2002 WO
200231857 Apr 2002 WO
2002031857 Apr 2002 WO
2002031857 Apr 2002 WO
2003029844 Apr 2003 WO
03042674 May 2003 WO
03051201 Jun 2003 WO
2003051201 Jun 2003 WO
2003051201 Jun 2003 WO
2003052397 Jun 2003 WO
2003065772 Aug 2003 WO
2003088302 Oct 2003 WO
03105159 Dec 2003 WO
2004008968 Jan 2004 WO
2004008970 Jan 2004 WO
2004010127 Jan 2004 WO
2004010127 Jan 2004 WO
2004010381 Jan 2004 WO
2004031755 Apr 2004 WO
2004031755 Apr 2004 WO
2004037088 May 2004 WO
2004042769 May 2004 WO
2004054329 Jun 2004 WO
2004072685 Aug 2004 WO
02004096050 Nov 2004 WO
2004096050 Nov 2004 WO
2004097344 Nov 2004 WO
2004097344 Nov 2004 WO
2004097386 Nov 2004 WO
2004097386 Nov 2004 WO
2004097886 Nov 2004 WO
2004097888 Nov 2004 WO
2004097888 Nov 2004 WO
2004097889 Nov 2004 WO
2004097889 Nov 2004 WO
2004105610 Dec 2004 WO
2004111625 Dec 2004 WO
2004097886 Jan 2005 WO
2005017566 Feb 2005 WO
2005037074 Apr 2005 WO
2005050256 Jun 2005 WO
2005050405 Jun 2005 WO
2005084351 Sep 2005 WO
2005095931 Oct 2005 WO
2005102170 Nov 2005 WO
2006027122 Mar 2006 WO
2006047718 May 2006 WO
2006069708 Jul 2006 WO
2006069708 Jul 2006 WO
2006074431 Jul 2006 WO
2006130630 Dec 2006 WO
2006130630 Dec 2006 WO
2006137919 Dec 2006 WO
2006135586 Feb 2007 WO
2007051418 May 2007 WO
2007068933 Jun 2007 WO
2007068933 Jun 2007 WO
2007076707 Jul 2007 WO
2007079675 Jul 2007 WO
2008018021 Feb 2008 WO
2008024825 Feb 2008 WO
2008027703 Mar 2008 WO
2008034232 Mar 2008 WO
2008068691 Jun 2008 WO
2008094305 Aug 2008 WO
2008115275 Sep 2008 WO
2008118568 Oct 2008 WO
2008118568 Oct 2008 WO
2009005932 Jan 2009 WO
2009006044 Jan 2009 WO
2009012453 Jan 2009 WO
2009012453 Jan 2009 WO
2009024817 Feb 2009 WO
2009025935 Feb 2009 WO
2009130491 Oct 2009 WO
2010007375 Jan 2010 WO
2010086653 Aug 2010 WO
2010097621 Sep 2010 WO
2010138574 Dec 2010 WO
2010138607 Dec 2010 WO
2010141659 Dec 2010 WO
2010145016 Dec 2010 WO
2012115629 Aug 2012 WO
20012115629 Aug 2012 WO
2013184103 Dec 2013 WO
Non-Patent Literature Citations (127)
Entry
US 5,987,079 A, 11/1999, Scott (withdrawn)
Third Party Submission Under 37 CFR 1.290 for U.S. Appl. No. 15/954,853, Apr. 19, 2019.
International Search Report for PCT/US18/27872, dated Jul. 23, 2018.
United States District Court Northern District of New York—Rapiscan Systems, Inc., Plaintiff, -vs- Surescan Corp., Surescan International Sales, Corp., Defendants., Civil Action No. 3:20-cv-00302-GLS-ML, Surescan's Disclosure of Non-Infringement, Invalidity and Unenforceability Contentions, Sep. 18, 2020.
“Commericalization 1997” Success Stories, US Army Small Business Innovation Research, Army SBIR Program Management Office, U.S. Army Research Office-Washington, 5001 Eisenhower Avenu, Alexandria, Virginia 22333, 1997.
William Michael Thompson's Thesis entitled “Source Firing Patterns and Reconstruction Algorithms for a Switched Source, Offset Detector CT Machine,” dated Dec. 31, 2010, and submitted to the University of Manchester (“Thompson Thesis”).
U.S. Appl. No. 12/097,422, filed Jun. 13, 2008.
Development of ultra-fast X-ray computed tomography scanner system, INS 98-43 6068772 A9823-8760J-016 (PHA); B9812-7510B-113 (EEA) NDN-174-0606-8771-7, Hori, K.; Fujimoto, T.; Kawanishi, K., Editor—Nalcioglu, O., Abbreviated Journal Title—1997 IEEE Nuclear Science Symposium, Conference Record (Cat. No. 97CH36135), Part No. vol. 2, 1997, pp. 1003-1008 vol. 2, 2 vol. xlviii+1761 page(s), ISBN-0 7803 4258 5.
International Search Report, PCT/GB2006/004684, dated May 23, 2007, CXR Ltd.
Sheen, David et al. ‘Three-Dimensional Millimeter-Wave Imaging for Concealed Weapon Detection’, Sep. 2001, IEEE Transactions on Microwave Theory and Techniques, vol. 49, No. 9, pp. 1581-1592.
Keevil, S.V., Lawinski, C.P. and Morton, E.J., 1987, “Measurement of the performance characteristics of anti-scatter grids.”, Phys. Med. Biol., 32(3), 397-403.
Morton, E.J., Webb, S., Bateman, J.E., Clarke, L.J. and Shelton, C.G., 1990, “Three-dimensional x-ray micro-tomography for medical and biological applications.”, Phys. Med. Biol., 35(7), 805-820.
Morton, E.J., Swindell, W., Lewis, D.G. and Evans, P.M., 1991, “A linear array scintillation-crystal photodiode detector for megavoltage imaging.”, Med. Phys., 18(4), 681-691.
Morton, E.J., Lewis, D.G. and Swindell, W., 1988, “A method for the assessment of radiotherapy treatment precision”, Brit. J. Radiol., Supplement 22, 25.
Swindell, W., Morton, E.J., Evans, P.M. and Lewis, D.G., 1991, “The design of megavoltage projection imaging systems: some theoretical aspects.”, Med. Phys., 18(5), 855-866.
Morton, E.J., Evans, P.M., Ferraro, M., Young, E.F. and Swindell, W., 1991, “A video frame store facility for an external beam radiotherapy treatment simulator.”, Brit. J. Radiol., 64, 747-750.
Antonuk, L.E., Yorkston, J., Kim, C.W., Huang, W., Morton, E.J., Longo, M.J. and Street, R.A., 1991, “Light response characteristics of amorphous silicon arrays for megavoltage and diagnostic imaging.”, Mat. Res. Soc. Sym. Proc., 219, 531-536.
Yorkston, J., Antonuk, L.E., Morton, E.J., Boudry, J., Huang, W., Kim, C.W., Longo, M.J. and Street, R.A., 1991, “The dynamic response of hydrogenated amorphous silicon imaging pixels.”, Mat. Res. Soc. Sym. Proc., 219, 173-178.
Evans, P.M., Gildersleve, J.Q., Morton, E.J., Swindell, W., Coles, R., Ferraro, M., Rawlings, C., Xiao, Z.R. and Dyer, J., 1992, “Image comparison techniques for use with megavoltage imaging systems.”, Brit. J. Radiol., 65, 701-709.
Morton, E.J., Webb, S., Bateman, J.E., Clarke, L.J. and Shelton, C.G., 1989, “The development of 3D x-ray micro-tomography at sub 100Ã?Âμm resolution with medical, industrial and biological applications.”, Presentation at IEE colloquium “Medical scanning and imaging techniques of value in non-destructive testing”, London, Nov. 3, 1989.
Antonuk, L.E., Boudry, J., Huang, W., McShan, D.L., Morton, E.J., Yorkston, J, Longo, M.J. and Street, R.A., 1992, “Demonstration of megavoltage and diagnostic x-ray imaging with hydrogenated amorphous silicon arrays.”, Med. Phys., 19(6), 1455-1466.
Gildersleve, J.Q., Swindell, W., Evans, P.M., Morton, E.J., Rawlings, C. and Dearnaley, D.P., 1991, “Verification of patient positioning during radiotherapy using an integrated megavoltage imaging system.”, in “Tumour Response Monitoring and Treatment Planning”, Proceedings of the International Symposium of the W. Vaillant Foundation on Advanced Radiation Therapy, Munich, Germany, Ed A. Breit (Berlin: Springer), 693-695.
Lewis, D.G., Evans, P.M., Morton, E.J., Swindell, W. and Xiao, X.R., 1992, “A megavoltage CT scanner for radiotherapy verification.”, Phys. Med. Biol., 37, 1985-1999.
Antonuk, L.E., Boudry, J., Kim, C.W., Longo, M.J., Morton, E.J., Yorkston, J. and Street, R.A., 1991, “Signal, noise and readout considerations in the development of amorphous silicon photodiode arrays for radiotherapy and diagnostic x-ray imaging.”, SPIE vol. 1443 Medical Imaging V: Image Physics, 108-119.
Antonuk, L.E., Yorkston, J., Huang, W., Boudry, J., Morton, E.J., Longo, M.J. and Street, R.A., 1992, “Radiation response characteristics of amorphous silicon arrays for megavoltage radiotherapy imaging.”, IEEE Trans. Nucl. Sci., 39,1069-1073.
Antonuk, L.E., Yorkston, J., Huang, W., Boudry, J., Morton, E.J., Longo, M.J. and Street, R.A., 1992, “Factors affecting image quality for megavoltage and diagnostic x-ray a-Si:H imaging arrays.”, Mat. Res. Soc. Sym. Proc., 258, 1069-1074.
Antonuk, L.E., Boudry, J., Yorkston, J., Morton, E.J., Huang, W. and Street, R.A., 1992, “Development of thin-film, flat-panel arrays for diagnostic and radiotherapy imaging.”, SPIE vol. 1651, Medical Imaging VI: Instrumentation, 94-105.
Yorkston, J., Antonuk, L.E., Seraji, N., Boudry, J., Huang, W., Morton, E.J., and Street, R.A., 1992, “Comparison of computer simulations with measurements from a-Si:H imaging arrays.”, Mat. Res. Soc. Sym. Proc., 258, 1163-1168.
Morton, E.J., Antonuk, L.E., Berry, J.E., Boudry, J., Huang, W., Mody, P., Yorkston, J. and Longo, M.J., 1992, “A CAMAC based data acquisition system for flat-panel image array readout”, Presentation at IEEE Nuclear Science Symposium, Orlando, Oct. 25-31, 1992.
Antonuk, L.E., Yorkston, J., Huang, W., Boudry, J., Morton, E.J. and Street, R.A., 1993, “Large area, flat-panel a-Si:H arrays for x-ray imaging.”, SPIE vol. 1896, Medical Imaging 1993: Physics of Medical Imaging, 18-29.
Morton, E.J., Antonuk, L.E., Berry, J.E., Huang, W., Mody, P. and Yorkston, J., 1994, “A data acquisition system for flat-panel imaging arrays”, IEEE Trans. Nucl. Sci., 41(4), 1150-1154.
Antonuk, L.E., Boudry, J., Huang, W., Lam, K.L., Morton, E.J., TenHaken, R.K., Yorkston, J. and Clinthorne, N.H., 1994, “Thin-film, flat-panel, composite imagers for projection and tomographic imaging”, IEEE Trans. Med. Im., 13(3), 482-490.
Gildersleve, J., Dearnaley, D., Evans, P., Morton, E.J. and Swindell, W., 1994, “Preliminary clinical performance of a scanning detector for rapid portal imaging”, Clin. Oncol., 6, 245-250.
Hess, R., De Antonis, P., Morton, E.J. and Gilboy, W.B., 1994, “Analysis of the pulse shapes obtained from single crystal CdZnTe radiation detectors”, Nucl. Inst. Meth., A353, 76-79.
DeAntonis, P., Morton, E.J., T. Menezes, 1996, “Measuring the bulk resistivity of CdZnTe single crystal detectors using a contactless alternating electric field method”, Nucl. Inst. Meth., A380, 157-159.
DeAntonis, P., Morton, E.J., Podd, F., 1996, “Infra-red microscopy of CdZnTe radiation detectors revealing their internal electric field structure under bias”, IEEE Trans. Nucl. Sci., 43(3), 1487-1490.
Tavora, L.M.N., Morgado, R.E., Estep, R.J., Rawool-Sullivan, M., Gilboy, W.B. and Morton, E.J., 1998, “One-sided imaging of large, dense, objects using the 511 keV photons from induced pair production”, IEEE Trans. Nucl. Sci., 45(3), 970-975.
Morton, E.J., 1995, “Archaeological potential of computerised tomography”, Presentation at IEE Colloquium on “NDT in archaeology and art”, London, May 25, 1995.
Tavora, L.M.N. and Morton, E.J., 1998, “Photon production using a low energy electron expansion of the EGS4 code system ”, Nucl. Inst. Meth., B143, 253-271.
Patel, D.C. and Morton, E.J., 1998, “Analysis of improved adiabatic pseudo-domino logic family”, Electron. Lett., 34(19), 1829-1830.
Kundu, A and Morton, E.J., 1999, “Numerical simulation of argon-methane gas filled proportional counters”, Nucl. Inst. Meth., A422, 286-290.
Luggar, R.D., Key, M.J., Morton, E.J. and Gilboy, W.B., 1999, “Energy dispersive X-ray scatter for measurement of oil/water ratios ”, Nucl. Inst. Meth., A422, 938-941.
Morton, E.J., Crockett, G.M., Sellin, P.J. and DeAntonis, P., 1999, “The charged particle response of CdZnTe radiation detectors”, Nucl. Inst. Meth., A422, 169-172.
Morton, E.J., Clark, R.J. and Crowley, C., 1999, “Factors affecting the spectral resolution of scintillation detectors”, Nucl. Inst. Meth., A422, 155-158.
Morton, E.J., Gaunt, J.C., Schoop, K., Swinhoe, M., 1996, “A new handheld nuclear material analyser for safeguards purposes”, Presentation at INMM annual meeting, Naples, Florida, Jul. 1996.
Hepworth, S., McJury, M., Oldham, M., Morton, E.J. and Doran, S.J., 1999, “Dose mapping of inhomogeneities positioned in radiosensitive polymer gels”, Nucl. Inst. Meth., A422, 756-760.
Morton, E.J., Luggar, R.D., Key, M.J., Kundu, A., Tavora, L.M.N. and Gilboy, W.B., 1999, “Development of a high speed X-ray tomography system for multiphase flow imaging”, IEEE Trans. Nucl. Sci., 46 III(1), 380-384.
Tavora, L.M.N., Morton, E.J., Santos, F.P. and Dias, T.H.V.T., 2000, “Simulation of X-ray tubes for imaging applications”, IEEE Trans. Nucl. Sci., 47, 1493-1497.
Tavora, L.M.N., Morton, E.J. and Gilboy, W.B., 2000, “Design considerations for transmission X-ray tubes operated at diagnostic energies”, J. Phys. D: Applied Physics, 33(19), 2497-2507.
Morton, E.J., Hossain, M.A., DeAntonis, P. and Ede, A.M.D., 2001, “Investigation of Au—CdZnTe contacts using photovoltaic measurements”, Nucl. Inst. Meth., A458, 558-562.
Ede, A.M.D., Morton, E.J. and DeAntonis, P., 2001, “Thin-film CdTe for imaging detector applications”, Nucl. Inst. Meth., A458, 7-11.
Tavora, L.M.N., Morton, E.J. and Gilboy, W.B., 2001, “Enhancing the ratio of fluorescence to bremsstrahlung radiation in X-ray tube spectra”, App. Rad. and Isotopes, 54(1), 59-72.
Menezes, T. and Morton, E.J., 2001, “A preamplifier with digital output for semiconductor detectors”, Nucl. Inst. Meth. A., A459, 303-318.
Johnson, D.R., Kyriou, J., Morton, E.J., Clifton, A.G. Fitzgerald, M. and MacSweeney, J.E., 2001, “Radiation protection in interventional radiology”, Clin. Rad., 56(2), 99-106.
Tavora, L.M.N., Gilboy, W.B. and Morton, E.J., 2001, “Monte Carlo studies of a novel X-ray tube anode design”, Rad. Phys. and Chem., 61, 527-529.
“Morton, E.J., 1998, “Is film dead: the flat plate revolution”, Keynote Talk, IPEM Annual Conference, Brighton, Sep. 14-17, 1998”\.
Luggar, R.D., Morton, E.J., Jenneson, P.M. and Key, M.J., 2001, “X-ray tomographic imaging in industrial process control”, Rad. Phys. Chem., 61, 785-787.
Luggar, R.D., Morton, E.J., Key, M.J., Jenneson, P.M. and Gilboy, W.B., 1999, “An electronically gated multi-emitter X-ray source for high speed tomography”, Presentation at SPIE Annual Meeting, Denver, Jul. 19-23, 1999.
Gregory, P.J., Hutchinson, D.J., Read, D.B., Jenneson, P.M., Gilboy, W.B. and Morton, E.J., 2001, “Non-invasive imaging of roots with high resolution X-ray microtomography”, Plant and Soil, 255(1), 351-359.
Kundu, A., Morton, E.J., Key, M.J. and Luggar, R.D., 1999, “Monte Carlo simulations of microgap gas-filled proportional counters”, Presentation at SPIE Annual Meeting, Denver, Jul. 19-23, 1999.
Hossain, M.A., Morton, E.J., and Ozsan, M.E., 2002, “Photo-electronic investigation of CdZnTe spectral detectors”, IEEE Trans. Nucl. Sci, 49(4), 1960-1964.
Panman, A., Morton, E.J., Kundu, A and Sellin, P.J., 1999, “Optical Monte Carlo transport in scintillators”, Presentation at SPIE Annual Meeting, Denver, Jul. 19-23, 1999.
Jenneson, P.M., Gilboy, W.B., Morton, E.J., and Gregory, P.J., 2003, “An X-ray micro-tomography system optimised for low dose study of living organisms”, App. Rad. Isotopes, 58, 177-181.
Key, M.J., Morton, E.J., Luggar, R.D. and Kundu, A., 2003, “Gas microstrip detectors for X-ray tomographic flow imaging”, Nucl. Inst. Meth., A496, 504-508.
Jenneson, P.M., Luggar, R.D., Morton, E.J., Gundogdu, O, and Tuzun, U, 2004, “Examining nanoparticle assemblies using high spatial resolution X-ray microtomography”, J. App. Phys, 96(5), 2889-2894.
Tavora, L.M., Gilboy, W.B. and Morton, E.J., 2000, “Influence of backscattered electrons on X-ray tube output”, Presentation at SPIE Annual Meeting, San Diego, Jul. 30-Aug. 3, 2000.
Wadeson, N., Morton, E.J., and Lionheart, W.B., 2010, “Scatter in an uncollimated x-ray CT machine based on a Geant4 Monte Carlo simulation”, SPIE Medical Imaging 2010: Physics of Medical Imaging, Feb. 15-18, 2010, San Diego, USA.
Morton, E.J., 2010, “Position sensitive detectors in security: Users perspective”, Invited talk, STFC meeting on position sensitive detectors, RAL, May 2010.
“Fiscan Multi-power X-ray Luggage Security Check Vehicle”, Wenxi Chen, et al., Technique for Police, No. 1, pp. 10-13, 20001231.
“SureScan X1000”, downloaded from https://web.archive.org/web/20031014195206/http://www.ensco.com:80/products/homeland/ssn/ssn_ovr.htm, downloaded Jul. 17, 2020.
H. Bruder, C. Suess, K. Stierstorfer, “Efficient extended field of view (eFOV) reconstruction techniques for multi-slice helical CT,” Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69132E, (Mar. 18, 2008).
International Search Report, PCT/US2012/40923, dated Sep. 21, 2012, Rapiscan Systems, Inc.
Written Opinion of the International Searching Authority for PCT/US2010/036183, dated Aug. 20, 2010.
Written Opinion of the International Searching Authority for PCT/US2012/40923, dated Sep. 21, 2012.
United States District Court Northern District of New York—Rapiscan Systems, Inc., Plaintiff, -vs- Surescan Corp., Surescan International Sales, Corp., Defendants., Civil Action No. 3:20-cv-00302-GLS-ML, Surescan's Answer to Rapiscan's First Amended Complaint for Patent Infringement, Affirmative Defenses, and Counterclaims, Jul. 6, 2020.
U.S. Appl. No. 15/235,130, filed Aug. 12, 2016.
U.S. Appl. No. 15/463,091, filed Mar. 20, 2017.
U.S. Appl. No. 15/593,943, filed May 12, 2017.
International Search Report for PCT/GB2004/001729, dated Aug. 12, 2004.
International Search Report for PCT/GB2004/001741, dated Mar. 3, 2005.
International Search Report for PCT/GB2004/001731, dated May 27, 2005.
International Search Report for PCT/GB2004/001732, dated Feb. 25, 2005.
STMicroelectronics, “Dual Full-Bridge Driver”, Datasheet for L298, 2000, pp. 1-13, XP002593095.
International Search Report, PCT/US2010/41871, dated Oct. 4, 2010, Rapiscan Systems, Inc.
Bruder et al. “Efficient Extended Field of View (eFOV) Reconstructuion Techniques for Multi-Slice Helical CT”, Medical Imaging 2008: Physics of Medical Imaging, edited by Jiang Hsieh, Ehsan Samei, Proc. of SPIE vol. 6913, 69132E, (2008).
International Search Report, PCT/GB2009/001760, dated Mar. 1, 2010, Rapiscan Systems, Inc.
International Search Report for PCT/US2010/037167, dated Sep. 7, 2010.
International Search Report, PCT/US2010/37167, dated Dec. 9, 2010, Rapiscan Security Products, Inc.
Dijon et al. “Towards a low-cost high-quality carbon-nanotube field-emission display”, Revised version of a paper presented at the 2004 SID International Symposium held May 25-27, 2004 in Seattle, Washington, Journal of the SID 12/4, 2004, pp. 373-378.
International Preliminary Report on Patentability for PCT/US12/40923 dated Dec. 9, 2014.
International Search Report for PCT/GB2010/050125, dated Sep. 1, 2010.
International Search Report for PCT/GB2009/051178, dated May 11, 2010.
“Efficient Extended Field of View (eFOW) Reconstruction Techniques for Multi-Slice Helical CT”, H. Bruder et al, Proceedings of SPIE, vol. 6913, Mar. 6, 2008, p. 69132E, XP055179726.
Crozier et al., Performance of Turbo-Codes with Relative prime and Golden Interleaving strategies, 1999, IEEE proceedings of the Sixth International mobile satellite conference, pp. 268-275.
Sunnegard, Combining Analytical and Iterative Reconstruction in Helical Cone-Beam CT, 2007, Linkoping Studies in Science and Technology Thesis No. 1301.
Kohler, A Projection Access scheme for Iterative Reconstruction Based on the Golden Section, 2004, IEEE, pp. 3961-3965.
Dolinar et al., Weight Distributions for Turbo Codes Using Random and Nonrandom Permutations, 1995, TDA Progress Report 42-122, pp. 56-65.
Mouhamedou, On Distance Measurement Methods for Turbo Codes, 2005, McGill University PhD. Thesis.
Bac et al., 3D Modelling and Segmentation with Discrete Curvatures, 2005, Journal of Medical Informatics & Technologies, vol. 9, pp. 13-24.
“SureScan X1000”, downloaded from https://web.archive.org/web/20030824070959/http://www.ensco.com/pdf/03.0090_SureScan_Web.pdf, downloaded Jul. 15, 2020.
U.S. Appl. No. 15/879,569, filed Jan. 25, 2018.
U.S. Appl. No. 12/787,930, filed May 26, 2010.
U.S. Appl. No. 61/181,068, filed May 26, 2009.
U.S. Appl. No. 61/155,572, filed Feb. 26, 2009.
U.S. Appl. No. 13/532,862, filed Jun. 26, 2012.
U.S. Appl. No. 13/405,117, filed Feb. 24, 2012.
U.S. Appl. No. 61/446,098, filed Feb. 24, 2011.
U.S. Appl. No. 60/619,339, filed Oct. 15, 2004.
U.S. Appl. No. 60/493,934, filed Aug. 8, 2003.
Definition of the term “ring” from Merriam Webster Dictionary Online, downloaded from: https://www.merriamwebster.com/dictionary/ring, downloaded Aug. 7, 2020.
Definition of the term “rotation” from Wikipedia, downloaded from: https://en.wikipedia.org/wiki/Rotation, downloaded Aug. 7, 2020.
International Search Report for PCT/US2010/036183, dated Aug. 20, 2010.
Great Britain Patent Application No. GB0903198.0, Filed Feb. 25, 2009.
Great Britain Patent Application No. GB0812864.7, Filed Jul. 15, 2008.
Great Britain Patent Application No. GB0525593.0, Filed Dec. 16, 2005.
Great Britain Patent Application No. GB0309379.6, Filed Apr. 25, 2003.
Great Britain Patent Application No. GB0309385.3, Filed Apr. 25, 2003.
Great Britain Patent Application No. GB0309374.7, Filed Apr. 25, 2003.
Great Britain Patent Application No. GB0309371.3, Filed Apr. 25, 2003.
Great Britain Patent Application No. GB0309383.8, Filed Apr. 25, 2003.
Great Britain Patent Application No. GB0309387.9, Filed Apr. 25, 2003.
International Search Report for PCT/GB2010/050318, dated Jul. 11, 2011.
International Search Report, PCT/GB2004/001747, dated Aug. 10, 2004.
International Search Report for PCT/GB2004/1751, dated Mar. 21, 2005.
International Search Report for PCT/GB2010/050438, dated Jun. 1, 2010.
International Search Report for PCT/US2011/025777, dated Jul. 26, 2011.
International Search Report, PCT/US2010/36221, dated Aug. 23, 2010, Rapiscan Security Productions, Inc.
Related Publications (1)
Number Date Country
20200378907 A1 Dec 2020 US
Continuations (5)
Number Date Country
Parent 16376918 Apr 2019 US
Child 16997309 US
Parent 14588732 Jan 2015 US
Child 16376918 US
Parent 13370941 Feb 2012 US
Child 14588732 US
Parent 12142005 Jun 2008 US
Child 13370941 US
Parent 12097422 US
Child 12142005 US