Abstract: An apparatus and method of processing X-ray projection data including spectral computed tomography (CT) projection data. The spectral CT data is decomposed into material projection lengths using a material-decomposition method that includes an initial-estimate method to provide an initial projection-lengths estimate. The initial-estimate method can include first reconstructing an image using non-spectral CT data, and then subdividing the reconstructed image into materials according to the relative attenuation density of areas within the reconstructed image (e.g., high attenuation areas correspond to a high attenuation material such as bone). The projection length estimates of each material are then obtained by forward projecting the corresponding subdivision of the reconstructed image. Also, the initial estimate can be obtained/refined by selecting the projection lengths with smallest cost-function value from randomly chosen projection lengths within a sample space.

Abstract: An apparatus and a method are provided for calculating an output spectrum of a photon-counting detector based on an incident spectrum. The apparatus includes processing circuitry to determine a plane extending from a top face of the photon-counting detector that includes regions that all possible incident rays will transverse; divide the determined plane into subregions; calculate a detector response function for each of the subregions; determine an overall detector response function by summing the calculated detector response function for each of the subregions and normalizing the summation by an area of the determined plane; and calculate the output spectrum based on the overall detector response function and the incident spectrum.

Abstract: A method and apparatus for estimating a parameter vector including a plurality of parameters of a detector response model of a photon-counting detector. The method includes calculating a modeled spectrum based on an input spectrum and an initial value of the plurality of parameters. For each detector, a difference between the normalized photon count of the measured spectrum and the normalized modeled spectrum is calculated. A root mean square error (RMSE) between the measured and modeled spectra is obtained by squaring the normalized difference and weighting the normalized difference by a weighting factor. The parameter vector is updated until an optimum RMSE value is achieved. Upon determining optimal values of the parameter vector, measured data that is obtained via a patient scan is corrected based on the optimal parameter vector.

Abstract: An apparatus and method of processing X-ray projection data obtained using photon-counting detectors and having multiple spectral components. The processing of the projection data includes correcting for nonlinear detector response, where the detector response model includes: pileup, ballistic deficit effects, polar effects, and characteristic X-ray escape. The processing of the projection data also includes a material decomposition mapping the projection data from spectral components into material components corresponding to high-Z and low-Z materials. The material decomposition includes a noise balancing process where the allocation of spectral components between a high-energy and a low-energy combination of spectral components is adjusted such that both high- and low-energy components have signal-to-noise ratios of similar magnitude. For computed tomography (CT) applications, material decomposition can be followed by image reconstruction and then image post-processing and presentation.

Abstract: A computed tomography (CT) apparatus and a method for determining response of a photon-counting detector of a CT scanner. Based on a count rate of an incident spectrum and a dead time parameter of the photon-counting detector, a highest pileup order that has a contribution towards an output spectrum of the photon-counting detector greater than a threshold corresponding to the pileup order is determined. In computing the overall output spectrum of the photon-counting detector, only the spectra corresponding to pileup orders lower than or equal to the highest pileup order are considered.

Abstract: An apparatus and method of processing X-ray projection data obtained using photon-counting detectors and having multiple spectral components. The processing of the projection data includes correcting for nonlinear detector response, where the detector response model includes: pileup, ballistic deficit effects, polar effects, and characteristic X-ray escape. The processing of the projection data also includes a material decomposition mapping the projection data from spectral components into material components corresponding to high-Z and low-Z materials. The material decomposition includes a noise balancing process where the allocation of spectral components between a high-energy and a low-energy combination of spectral components is adjusted such that both high- and low-energy components have signal-to-noise ratios of similar magnitude. For computed tomography (CT) applications, material decomposition can be followed by image reconstruction and then image post-processing and presentation.

Abstract: An apparatus and method of processing X-ray projection data including spectral computed tomography (CT) projection data. The spectral CT data is decomposed into material projection lengths using a material-decomposition method that includes an initial-estimate method to provide an initial projection-lengths estimate. The initial-estimate method can include first reconstructing an image using non-spectral CT data, and then subdividing the reconstructed image into materials according to the relative attenuation density of areas within the reconstructed image (e.g., high attenuation areas correspond to a high attenuation material such as bone). The projection length estimates of each material are then obtained by forward projecting the corresponding subdivision of the reconstructed image. Also, the initial estimate can be obtained/refined by selecting the projection lengths with smallest cost-function value from randomly chosen projection lengths within a sample space.

Abstract: A computed tomography (CT) apparatus and a method for determining response of a photon-counting detector of a CT scanner. Based on a count rate of an incident spectrum and a dead time parameter of the photon-counting detector, a highest pileup order that has a contribution towards an output spectrum of the photon-counting detector greater than a threshold corresponding to the pileup order is determined. In computing the overall output spectrum of the photon-counting detector, only the spectra corresponding to pileup orders lower than or equal to the highest pileup order are considered.

Abstract: An apparatus and a method are provided for calculating an output spectrum of a photon-counting detector based on an incident spectrum. The apparatus includes processing circuitry to determine a plane extending from a top face of the photon-counting detector that includes regions that all possible incident rays will transverse; divide the determined plane into subregions; calculate a detector response function for each of the subregions; determine an overall detector response function by summing the calculated detector response function for each of the subregions and normalizing the summation by an area of the determined plane; and calculate the output spectrum based on the overall detector response function and the incident spectrum.

Abstract: A method and apparatus for estimating a parameter vector including a plurality of parameters of a detector response model of a photon-counting detector. The method includes calculating a modeled spectrum based on an input spectrum and an initial value of the plurality of parameters. For each detector, a difference between the normalized photon count of the measured spectrum and the normalized modeled spectrum is calculated. A root mean square error (RMSE) between the measured and modeled spectra is obtained by squaring the normalized difference and weighting the normalized difference by a weighting factor. The parameter vector is updated until an optimum RMSE value is achieved. Upon determining optimal values of the parameter vector, measured data that is obtained via a patient scan is corrected based on the optimal parameter vector.

Abstract: A method and apparatus for determining a parameter vector that includes a plurality of parameters of a detector pileup model of a photon-counting detector, the detector pileup model being used for pileup correction for a spectral computed-tomography scanner. The method includes setting values of the parameters, the parameters including a dead time parameter and individual probabilities of different pileup events, the probabilities including a probability of single photon events, a probability of double quasi-coincident photon events, and a probability of at least three quasi-coincident photon events. The method include determining, using (1) a detector response model, (2) an incident spectrum, and (3) the set values of the parameter vector, a plurality of component spectra, each component spectrum corresponding to one of the individual probabilities of the different pileup events, and summing the plurality of component spectra to generate an output spectrum.

Abstract: A method and apparatus for determining a parameter vector that includes a plurality of parameters of a detector pileup model of a photon-counting detector, the detector pileup model being used for pileup correction for a spectral computed-tomography scanner. The method includes setting values of the parameters, the parameters including a dead time parameter and individual probabilities of different pileup events, the probabilities including a probability of single photon events, a probability of double quasi-coincident photon events, and a probability of at least three quasi-coincident photon events. The method include determining, using (1) a detector response model, (2) an incident spectrum, and (3) the set values of the parameter vector, a plurality of component spectra, each component spectrum corresponding to one of the individual probabilities of the different pileup events, and summing the plurality of component spectra to generate an output spectrum.