Abstract: Methods and systems are provided for improving image quality with three-dimensional (3D) scout scans for computed tomography (CT) imaging. In one embodiment, a method comprises reconstructing an image from projection data acquired during a diagnostic scan of a patient with corrections based on scout projection data acquired during a 3D scout scan of the patient. In this way, the image quality of a diagnostic image can be improved by using 3D scout data to correct projection data or image data.

Abstract: A signal processing method is disclosed, which includes detecting a total intensity of X-rays passing through an object comprising multiple materials; obtaining at least one set of basis information of basis material information of the multiple materials and basis component information of photon-electric absorption basis component and Compton scattering basis component of the object; estimating a scatter intensity component of the detected X-rays based on the at least one set of basis information and the detected total intensity; and obtaining an intensity estimate of primary X-rays incident on a detector based on the detected total intensity and the estimated scatter intensity component. An imaging system adopting the above signal processing method is also disclosed.

Abstract: A method relates to the use of deep learning techniques, which may be implemented using trained neural networks (50), to estimate various types of missing projection or other unreconstructed data. Similarly, the method may also be employed to replace or correct corrupted or erroneous projection data as opposed to estimating missing projection data.

Abstract: A computed tomography (CT) imaging system and method, wherein the system includes an x-ray source that is operable to emit a beam of x-rays from a focal spot and move a spot position of the focal spot. The system also includes a detector assembly that is configured to detect the x-rays attenuated by the object. At least one processing unit is configured to execute programmed instructions stored in memory. The at least one processing unit is configured to direct the x-ray source to emit different beams of the x-rays at different energy levels and to receive data from the detector assembly that are representative of detection of the x-rays emitted at the different energy levels. The at least one processing unit is also configured to direct the x-ray source to move the focal spot such that the focal spot is at different spot positions while the different beams are emitted.

Abstract: The present approaches relates to the use of silicon-based energy-discriminating, photon-counting detectors, such as for use in X-ray based imaging including computed tomography. The described approaches address the resolution and classification of X-ray photons affected by Compton scatter, which may be detected as having energy levels below their proper level due to collision or deflection events.

Abstract: The present approach relates to the use of detector elements (i.e., reference detector pixels) positioned under septa of an anti-scatter collimator. Signals detected by the reference detector pixels may be used to correct for charging-sharing events with adjacent pixels and/or to characterize or correct for focal spot misalignment either in real time or as a calibration step.

Abstract: A method for imaging an object to be reconstructed includes acquiring projection data corresponding to the object. Furthermore, the method includes generating a measured sinogram based on the acquired projection data and formulating a forward model, where the forward model is representative of a characteristic of the imaging system. In addition, the method includes generating an estimated sinogram based on an estimated image of the object and the forward model and formulating a statistical model based on at least one of pile-up characteristics and dead time characteristics of a detector of the imaging system. Moreover, the method includes determining an update corresponding to the estimated image based on the statistical model, the measured sinogram, and the estimated sinogram and updating the estimated image based on the determined update to generate an updated image of the object. Additionally, the method includes outputting a final image of the object.

Abstract: A method for imaging an object to be reconstructed includes acquiring projection data corresponding to the object. Furthermore, the method includes generating a measured sinogram based on the acquired projection data and formulating a forward model, where the forward model is representative of a characteristic of the imaging system. In addition, the method includes generating an estimated sinogram based on an estimated image of the object and the forward model and formulating a statistical model based on at least one of pile-up characteristics and dead time characteristics of a detector of the imaging system. Moreover, the method includes determining an update corresponding to the estimated image based on the statistical model, the measured sinogram, and the estimated sinogram and updating the estimated image based on the determined update to generate an updated image of the object. Additionally, the method includes outputting a final image of the object.

Abstract: A signal processing method is disclosed, which includes detecting a total intensity of X-rays passing through an object comprising multiple materials; obtaining at least one set of basis information of basis material information of the multiple materials and basis component information of photon-electric absorption basis component and Compton scattering basis component of the object; estimating a scatter intensity component of the detected X-rays based on the at least one set of basis information and the detected total intensity; and obtaining an intensity estimate of primary X-rays incident on a detector based on the detected total intensity and the estimated scatter intensity component. An imaging system adopting the above signal processing method is also disclosed.

Abstract: The present approach relates to scatter correction of signals acquired using radiation detectors on a pixel-by-pixel basis. In certain implementations, the systems and methods disclosed herein facilitate scatter correction for signals generated using a detector having segmented detector elements, such as may be present in an energy-resolving, photon-counting CT imaging system.

Abstract: The present approach relates to avoiding azimuthal blur in a computed tomography context, such as in dual energy imaging with fast kV switching. In accordance with certain aspects, the focal spot position is held stationary in the patient coordinate system within each respective view and the detector signals within the view are summed. In one embodiment, this results in the low and high energy views within the signal being collected from the same position within the patient coordinate system.

Abstract: A signal processing method is disclosed, which includes detecting a total intensity of X-rays passing through an object comprising multiple materials; obtaining at least one set of basis information of basis material information of the multiple materials and basis component information of photon-electric absorption basis component and Compton scattering basis component of the object; estimating a scatter intensity component of the detected X-rays based on the at least one set of basis information and the detected total intensity; and obtaining an intensity estimate of primary X-rays incident on a detector based on the detected total intensity and the estimated scatter intensity component. An imaging system adopting the above signal processing method is also disclosed.

Abstract: A detector is described having readout electronics integrated in the photodetector layer. The detector may be configured to acquire both energy-integrated and photon-counting data. In one implementation, the detector is also configured with control logic to select between the jointly generated photon-counting and energy-integrated data.

Abstract: There is set forth herein a method including performing with an X-ray detector array of a CT imaging system one or more calibration scans, wherein the one or more calibration scans include obtaining for each element of the first through Nth elements of the X-ray detector array one or more calibration measurements; and updating a spectral response model for each element of the first through Nth elements using the one or more calibration measurements. In another aspect, a CT imaging system can perform imaging, e.g. including material decomposition (MD) imaging, using updated spectral response models for elements of an X-ray detector array. The spectral response models can be updated using a calibration process so that different elements of an X-ray detector array have different spectral response models.

Abstract: A computed tomography (CT) imaging system and method, wherein the system includes an x-ray source that is operable to emit a beam of x-rays from a focal spot and move a spot position of the focal spot. The system also includes a detector assembly that is configured to detect the x-rays attenuated by the object. At least one processing unit is configured to execute programmed instructions stored in memory. The at least one processing unit is configured to direct the x-ray source to emit different beams of the x-rays at different energy levels and to receive data from the detector assembly that are representative of detection of the x-rays emitted at the different energy levels. The at least one processing unit is also configured to direct the x-ray source to move the focal spot such that the focal spot is at different spot positions while the different beams are emitted.

Abstract: The present approaches relates to the use of silicon-based energy-discriminating, photon-counting detectors, such as for use in X-ray based imaging including computed tomography. The described approaches address the resolution and classification of X-ray photons affected by Compton scatter, which may be detected as having energy levels below their proper level due to collision or deflection events.

Abstract: A method relates to the use of deep learning techniques, which may be implemented using trained neural networks (50), to estimate various types of missing projection or other unreconstructed data. Similarly, the method may also be employed to replace or correct corrupted or erroneous projection data as opposed to estimating missing projection data.

Abstract: The present approaches relates to the use of silicon-based energy-discriminating, photon-counting detectors, such as for use in X-ray based imaging including computed tomography. The described approaches address the resolution and classification of X-ray photons affected by Compton scatter, which may be detected as having energy levels below their proper level due to collision or deflection events.

Abstract: The present approach relates to avoiding azimuthal blur in a computed tomography context, such as in dual energy imaging with fast kV switching. In accordance with certain aspects, the focal spot position is held stationary in the patient coordinate system within each respective view and the detector signals within the view are summed. In one embodiment, this results in the low and high energy views within the signal being collected from the same position within the patient coordinate system.

Abstract: Methods and systems are provided for improving image quality with three-dimensional (3D) scout scans for computed tomography (CT) imaging. In one embodiment, a method comprises reconstructing an image from projection data acquired during a diagnostic scan of a patient with corrections based on scout projection data acquired during a 3D scout scan of the patient. In this way, the image quality of a diagnostic image can be improved by using 3D scout data to correct projection data or image data.