Abstract: Acquisition of X-ray transmission data at three or more energy levels is described. Various implementations utilize generator waveforms that utilize fast-switching, slow-switching, or a combination of fast- and slow-switching to transition between X-ray energy levels. In addition, various sampling arrangements for sampling and/or binning three or more energy levels of X-ray transmission data are discussed. The use of these data in subsequent processing steps, such for material decomposition and/or improvement of dual-energy material decomposition processing, are also described.

Abstract: A method includes receiving, with at least one processor, a first projection dataset corresponding to X-rays at a first energy level projected towards a subject at a first set of view angles and receiving, with the at least one processor, a second projection dataset corresponding to X-rays at a second energy level projected towards the subject at a second set of view angles. The method further includes identifying, with the at least one processor, a metal trace from at least one of the first projection dataset and the second projection dataset. Moreover, the method includes converting, with the at least one processor, at least a portion of the first projection dataset to a pseudo dataset at the second energy level. The method also includes generating, with the at least one processor, a final image of the subject based on the second projection dataset, the pseudo dataset, and the metal trace.

Abstract: A computationally efficient dictionary learning-based term is employed in an iterative reconstruction framework to keep more spatial information than two-dimensional dictionary learning and require less computational cost than three-dimensional dictionary learning. In one such implementation, a non-local regularization algorithm is employed in an MBIR context (such as in a low dose CT image reconstruction context) based on dictionary learning in which dictionaries from different directions (e.g., x,y-plane, y,z-plane, x,z-plane) are employed and the sparse coefficients calculated accordingly. In this manner, spatial information from all three directions is retained and computational cost is constrained.

Abstract: Approaches related to performing calibration of a CT scanner or of processes (e.g., correction and/or reconstruction) performed on acquired CT scan data are described. In certain described approaches, calibration is attained without performing a calibration scan using a dedicated calibration phantom. In certain embodiments, calibration is performed using a feature intrinsic to the imaged object, such as a jacket disposed about a drilled core sample.

Abstract: A framework for an iterative reconstruction algorithm is described which combines two or more of an ordered subset method, a preconditioner method, and a nested loop method. In one type of implementation a nested loop (NL) structure is employed where the inner loop sub-problems are solved using ordered subset (OS) methods. The inner loop may be solved using OS and a preconditioner method. In other implementations, the inner loop problems are created by augmented Lagrangian methods and then solved using OS method.

Abstract: Methods, systems, and non-transitory computer readable media for image reconstruction are presented. Measured data corresponding to a subject is received. A preliminary image update in a particular iteration is determined based on one or more image variables computed using at least a subset of the measured data in the particular iteration. Additionally, at least one momentum term is determined based on the one or more image variables computed in the particular iteration and/or one or more further image variables computed in one or more iterations preceding the particular iteration. Further, a subsequent image update is determined using the preliminary image update and the momentum term. The preliminary image update and/or the subsequent image update are iteratively computed for a plurality of iterations until one or more termination criteria are satisfied.

Abstract: An imaging method includes executing a low-dose preparatory scan to an object by applying tube voltages and tube currents in an x-ray source, and generating a first image of the object corresponding to the low-dose preparatory scan. The method further includes generating image quality estimates and dose estimates view by view at least based on the first image. The method includes optimizing the tube voltages and the tube currents to generate optimal profiles for the tube voltage and the tube current. At least one of the optimal profiles for the tube voltage and the tube current is generated based on the image quality estimates and the dose estimates. The method includes executing an acquisition scan by applying the tube voltages and the tube currents based on the optimal profiles and generating a second image of the object corresponding to the acquisition scan. An imaging system is also provided.

Abstract: The use of the channelized preconditioners in iterative reconstruction is disclosed. In certain embodiments, different channels correspond to different frequency sub-bands and the output of the different channels can be combined to update an image estimate used in the iterative reconstruction process. While individual channels may be relatively simple, the combined channels can represent complex spatial variant operations. The use of channelized preconditioners allows empirical adjustment of individual channels.

Abstract: Approaches for acquiring CT image data corresponding to a full scan, but at a reduced dose are disclosed. In one implementation, X-ray tube current modulation is employed to reduce the effective dose. In other implementations, acquisition of sparse views, z-collimation, and two-rotation acquisition protocols may be employed to achieve a reduced dose relative to a full-scan acquisition protocol.

Abstract: A method includes receiving, with at least one processor, a first projection dataset corresponding to X-rays at a first energy level projected towards a subject at a first set of view angles and receiving, with the at least one processor, a second projection dataset corresponding to X-rays at a second energy level projected towards the subject at a second set of view angles. The method further includes identifying, with the at least one processor, a metal trace from at least one of the first projection dataset and the second projection dataset. Moreover, the method includes converting, with the at least one processor, at least a portion of the first projection dataset to a pseudo dataset at the second energy level. The method also includes generating, with the at least one processor, a final image of the subject based on the second projection dataset, the pseudo dataset, and the metal trace.

Abstract: Methods and systems are provided for correcting artifacts in iterative reconstruction processes. In certain embodiments, weighting schemes may be applied such that less than all of the available scan or projection data is utilized in the iterative reconstruction. In this manner, inconsistencies in the data undergoing reconstruction may be reduced.

Abstract: A system and method for CT projection extrapolation are provided. The method comprises receiving a CT projection for extrapolation. The method also comprises selecting a target patch comprising at least one pixel of a row to be extrapolated. The method further comprises generating a correlation profile between the target patch and one or more source patches, wherein the source patches comprise measured pixels in the CT projection in one or more rows adjacent to the target patch. The projection data is generated for at least one pixel of the target patch based on the correlation profile and the measured pixels of at least one of the source patches.

Abstract: Embodiments of the disclosure relate to projection-based volumetric dose estimation for X-ray systems, such as X-ray imaging systems. For example, in one embodiment, an X-ray system is capable of estimating an X-ray dose based on an energy interaction of the X-rays with respective portions of an object. In another embodiment, the X-ray dose estimate may be provided on a per voxel, per region, and/or per organ basis.

Abstract: Embodiments of the disclosure relate to projection-based dose estimation for X-ray systems, such as X-ray imaging systems. For example, in one embodiment, an X-ray system is capable of estimating an X-ray dose based on an intensity profile of the detected X-rays that have passed through a scanned object and an estimated mass of the object. In one embodiment, the intensity profile may be compared to a baseline scan to acquire an estimate of energy interaction with the object.

Abstract: An approach is disclosed for acquiring multi-sector computed tomography scan data. The approach includes activating an X-ray source during heartbeats of a patient to acquire projection data over a limited angular range for each heartbeat. The projection data acquired over the different is combined. An image having good temporal resolution is reconstructed using the combined projection data.

Abstract: A method for reconstructing an image of an object that includes a plurality of image elements. The method includes accessing image data associated with a plurality of image elements, and reconstructing an image of the object by optimizing an objective function, where the objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. The algorithm is composed of nested iterative loops, in which an inner loop iteratively optimizes an objective function approximating the outer loop objective function, and an outer loop that utilizes the solution of the inner loop to optimize the original objective function.

Abstract: A method is provided for iteratively reconstructing an image of an object. The method includes accessing measurement data associated with the image, and using a simultaneous algorithm to reconstruct the image. Using the simultaneous algorithm to reconstruct the image includes determining a scaling factor that is voxel-dependent, and applying the voxel-dependent scaling factor to a gradient of an objective function to reconstruct the image.

Abstract: The use of the channelized preconditioners in iterative reconstruction is disclosed. In certain embodiments, different channels correspond to different frequency sub-bands and the output of the different channels can be combined to update an image estimate used in the iterative reconstruction process. While individual channels may be relatively simple, the combined channels can represent complex spatial variant operations. The use of channelized preconditioners allows empirical adjustment of individual channels.

Abstract: A framework for an iterative reconstruction algorithm is described which combines two or more of an ordered subset method, a preconditioner method, and a nested loop method. In one type of implementation a nested loop (NL) structure is employed where the inner loop sub-problems are solved using ordered subset (OS) methods. The inner loop may be solved using OS and a preconditioner method. In other implementations, the inner loop problems are created by augmented Lagrangian methods and then solved using OS method.

Abstract: Methods are provided for iteratively reconstructing an image signal to generate a reconstructed image signal. In one embodiment, sub-iterations of each iteration are performed on pixel or voxel subsets. The subsets may be composed of neighboring or spatially separated pixel or voxels and may extend in the z-direction. In one embodiment, an update step of the iterative reconstruction involves the direct inversion of an approximation of a Hessian matrix associated with the respective subsets. In further embodiments, non-negativity or other limitations or constraints on update values may be enforced.