Abstract: A method of and a system for sharp object detection using computed tomography images are provided. The method comprises identifying voxels corresponding to individual objects; performing eigen-analysis and generating eigen-projection of an identified object; computing an axial concavity ratio of the identified object; computing a pointness measurement of the identified object; computing a flat area of the identified object; calculating a sharpness score of the identified object; and declaring the identified object as a threat if the sharpness score is greater than a pre-defined threshold.

Abstract: A method of and system for detecting threat objects represented in 3D CT data uses knowledge of one or more predefined shapes of the threat objects. An object represented by CT data for a region is identified. A two-dimensional projection of the object along a principal axis of the object is generated. A contour of the object boundary in the projection image is computed. A shape histogram is computed from the extracted contour. A difference measure between the extracted shape histogram and a set of pre-computed threat shape histograms is computed. A declaration of a threat object is made if the difference measure is less than a pre-defined threshold.

Abstract: A method of and a system for spectral correction in multi-energy computed tomography are provided to correct reconstructed images, including high-energy CT images and Z (effective atomic number) images, for spectral variations, which include time variations on a scanner due to HVPS drift and scanner to scanner variations due to the beamline component differences. The method uses a copper filter mounted on the detector array for tracking the spectral changes. The method comprises: generating copper ratios; computing working air tables; calculating scales and offsets; and correcting high-energy CT images and Z images using calculated scales and offsets. The method further includes an off-line calibration procedure to generate necessary parameters for the online correction.

Abstract: A method of and a system for computing Z (effective atomic number) images from projection data are provided, wherein the projections are acquired using at least two x-ray spectra for a set of scanned objects, including a set of low energy projections and a set of high energy projections; the method comprises decomposing the low energy projections and high energy projections into photoelectric projections, reconstructing the photoelectric projections into photoelectric images, reconstructing one of the two sets of projections into CT images, and computing Z images from the CT images and the photoelectric images with parameters obtained from a calibration procedure.

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

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

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

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

Abstract: A method of and a system for stabilizing High Voltage Power Supply (HVPS) DC and AC voltages in multi-energy X-ray computed tomography scanners are provided. The method comprises generating filter ratios, computing DC and AC voltages, and feeding back the computed DC and AC voltages to the commanded voltages. The filtered ratios including an air ratio and a copper ratio are modeled as nonlinear functions of the DC and AC voltages. Computing DC and AC voltages include computing an m-ratio and an n-ratio. The parameters of the nonlinear model comprise an exponent parameter and a set of polynomial coefficients. The parameters are determined by a calibration procedure, which performs scanning at different combination of DC and AC voltages. The optimal parameters are obtained through a nonlinear least square minimization, which is solved through a brute force search over the exponent parameter and a closed form solution of the polynomial coefficients.

Abstract: Method of and system for adaptive scatter correction in the absence of scatter detectors in multi-energy computed tomography are provided, wherein input projection data acquired using at least two x-ray spectra for scanned objects may include a set of low energy projections and a set of high energy projections; wherein a low-pass filter of variable size is provided; the method comprises estimating the size of the low-pass filter; computing amounts of scatter; and correcting both sets of projections for scatter. The estimation of low-pass filter size comprises thresholding high energy projections into binary projections; filtering the binary projections; finding the maximum of the filtered binary projections; calculating the low-pass filter size from the found maximum. The computation of amounts of scatter comprises exponentiating input projections; low-pass filtering the exponentiated projections with the estimated filter size; computing the amounts of scatter from the filtered projections.

Abstract: A method of and a system for stabilizing High Voltage Power Supply (HVPS) DC and AC voltages in multi-energy X-ray computed tomography scanners are provided. The method comprises generating filter ratios, computing DC and AC voltages, and feeding back the computed DC and AC voltages to the commanded voltages. The filtered ratios including an air ratio and a copper ratio are modeled as nonlinear functions of the DC and AC voltages. Computing DC and AC voltages include computing an m-ratio and an n-ratio. The parameters of the nonlinear model comprise an exponent parameter and a set of polynomial coefficients. The parameters are determined by a calibration procedure, which performs scanning at different combination of DC and AC voltages. The optimal parameters are obtained through a nonlinear least square minimization, which is solved through a brute force search over the exponent parameter and a closed form solution of the polynomial coefficients.

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

Abstract: A method of and a system for spectral correction in multi-energy computed tomography are provided to correct reconstructed images, including high-energy CT images and Z (effective atomic number) images, for spectral variations, which include time variations on a scanner due to HVPS drift and scanner to scanner variations due to the beamline component differences. The method uses a copper filter mounted on the detector array for tracking the spectral changes. The method comprises: generating copper ratios; computing working air tables; calculating scales and offsets; and correcting high-energy CT images and Z images using calculated scales and offsets. The method further includes an off-line calibration procedure to generate necessary parameters for the online correction.

Abstract: A method of and a system for sharp object detection using computed tomography images are provided. The method comprises identifying voxels corresponding to individual objects; performing eigen-analysis and generating eigen-projection of an identified object; computing an axial concavity ratio of the identified object; computing a pointness measurement of the identified object; computing a flat area of the identified object; calculating a sharpness score of the identified object; and declaring the identified object as a threat if the sharpness score is greater than a pre-defined threshold.

Abstract: Method of and system for adaptive scatter correction in the absence of scatter detectors in multi-energy computed tomography are provided, wherein input projection data acquired using at least two x-ray spectra for scanned objects may include a set of low energy projections and a set of high energy projections; wherein a low-pass filter of variable size is provided; the method comprises estimating the size of the low-pass filter; computing amounts of scatter; and correcting both sets of projections for scatter. The estimation of low-pass filter size comprises thresholding high energy projections into binary projections; filtering the binary projections; finding the maximum of the filtered binary projections; calculating the low-pass filter size from the found maximum. The computation of amounts of scatter comprises exponentiating input projections; low-pass filtering the exponentiated projections with the estimated filter size; computing the amounts of scatter from the filtered projections.

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

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

Abstract: A method of and a system for computing Z (effective atomic number) images from projection data are provided, wherein the projections are acquired using at least two x-ray spectra for a set of scanned objects, including a set of low energy projections and a set of high energy projections; the method comprises decomposing the low energy projections and high energy projections into photoelectric projections, reconstructing the photoelectric projections into photoelectric images, reconstructing one of the two sets of projections into CT images, and computing Z images from the CT images and the photoelectric images with parameters obtained from a calibration procedure.

Abstract: A method of and system for detecting threat objects represented in 3D CT data uses knowledge of one or more predefined shapes of the threat objects. An object represented by CT data for a region is identified. A two-dimensional projection of the object along a principal axis of the object is generated. A contour of the object boundary in the projection image is computed. A shape histogram is computed from the extracted contour. A difference measure between the extracted shape histogram and a set of pre-computed threat shape histograms is computed. A declaration of a threat object is made if the difference measure is less than a pre-defined threshold.