Abstract: Techniques for radiomics standardization for patient scan data obtained by a particular imaging device are presented. The techniques include acquiring, using the particular imaging machine, the patient scan data; obtaining unstandardized radiomics for the patient scan data; recovering standardized radiomics for the patient scan data based on at least: the patient scan data, the unstandardized radiomics for the patient scan data, and calibration phantom data for the particular machine obtained using at least one calibration phantom; and outputting the standardized radiomics.

Abstract: The present invention is directed to multiple aperture devices (MADs) for beam shaping in x-ray imaging. Two or more of these binary filters can be placed in an x-ray beam in series to permit a large number of x-ray fluence profiles. However, the relationship between particular MAD designs and the achievable fluence patterns is complex. The present invention includes mathematical and physical models that are used within an optimization framework to find optimal MAD designs. Specifically, given a set of target fluence patterns, the present invention finds, for example, a dual MAD design that is a “best fit” in generating the desired fluence patterns. This process provides a solution for both the design of MAD filters as well as the control actuation that is required (relative motion between MADs) that needs to be specified as part of the operation of a MAD-based fluence field modulation system.

Abstract: The present invention is directed to spatial-spectral filtering for multi-material CT decomposition. The invention includes a specialized filter that spectrally shapes an x-ray beam into a number of beamlets with different spectra. The filter allows decomposition of an object/anatomy into different material categories (including different biological types: muscle, fat, etc. or exogenous contrast agents that have been introduced: e.g iodine, gadolinium, etc.). The x-ray beam is spectrally modulated across the face of the detector using a repeating pattern of filter materials. Such spatial-spectral filters allow for collection of many different spectral channels using “source-side” control. However, in contrast to other spectral techniques that provide mathematically complete projection data, spatial-spectral filtered data is sparse in each spectral channel—making traditional projection-domain or image-domain material decomposition difficult to apply.

Abstract: In some implementations, a device may obtain scan information associated with scanning a section of a body that includes an object within tissue of the section. The device may determine a region of the section that is likely to be represented by an artifact in an image obtained using a first scanning type of a medical image device. The device may determine a plurality of scan patterns for scanning the region using a second scanning type. The device may determine, for the plurality of scan patterns, individual scan scores associated with scanning the region. The device may select, based on the individual scan scores, an optimal scan pattern from the plurality of scan patterns. The device may transmit the optimal scan pattern to the medical imaging device to permit the medical imaging device to scan the section to obtain optimized image data associated with the region.

Abstract: The present invention is directed to multiple aperture devices (MADs) for beam shaping in x-ray imaging. Two or more of these binary filters can be placed in an x-ray beam in series to permit a large number of x-ray fluence profiles. However, the relationship between particular MAD designs and the achievable fluence patterns is complex. The present invention includes mathematical and physical models that are used within an optimization framework to find optimal MAD designs. Specifically, given a set of target fluence patterns, the present invention finds, for example, a dual MAD design that is a “best fit” in generating the desired fluence patterns. This process provides a solution for both the design of MAD filters as well as the control actuation that is required (relative motion between MADs) that needs to be specified as part of the operation of a MAD-based fluence field modulation system.

Abstract: The present invention is directed to spatial-spectral filtering for multi-material CT decomposition. The invention includes a specialized filter that spectrally shapes an x-ray beam into a number of beamlets with different spectra. The filter allows decomposition of an object/anatomy into different material categories (including different biological types: muscle, fat, etc. or exogenous contrast agents that have been introduced: e.g iodine, gadolinium, etc.). The x-ray beam is spectrally modulated across the face of the detector using a repeating pattern of filter materials. Such spatial-spectral filters allow for collection of many different spectral channels using “source-side” control. However, in contrast to other spectral techniques that provide mathematically complete projection data, spatial-spectral filtered data is sparse in each spectral channel—making traditional projection-domain or image-domain material decomposition difficult to apply.

Abstract: The present invention is directed to a method of multi-motion compensation for high-quality cone-beam CT of the head. A multi-stage approach is incorporated that includes a pre-conditioning stage in which an initial estimation of the motion trajectory is obtained with 3D-2D registration using the motion-contaminated CBCT and projection data. In the present invention, the motion-contaminated CBCT is used as a basis for 3D-2D registration in the pre-conditioning stage to capture large amplitude, rapid movements of the head and provide better initialization of the autofocus solution.

Abstract: Techniques for computed tomography (CT) image reconstruction are presented. The techniques can include acquiring, by a detector grid of a computed tomography system, detector signals for a location within an object of interest representing a voxel, where each detector signal of a plurality of the detector signals is obtained from an x-ray passing through the location at a different viewing angle; reconstructing a three-dimensional representation of at least the object of interest, the three-dimensional representation comprising the voxel, where the reconstructing comprises computationally perturbing a location of each detector signal of the plurality of detector signals within the detector grid, where the computationally perturbing corresponds to randomly perturbing a location of the x-ray within the voxel; and outputting the three-dimensional representation.

Abstract: A device receives a prior image associated with an anatomy of interest, and receives measurements associated with the anatomy of interest. The device processes the prior image and the measurements, with a reconstruction of difference technique, to generate a difference image associated with the anatomy of interest, wherein the difference image indicates one or more differences between the prior image and the measurements. The device generates, based on the difference image and the prior image, a final image associated with the anatomy of interest, and provides, for display, the final image associated with the anatomy of interest.

Abstract: The present invention is directed to a method for enabling volumetric image reconstruction from unknown projection geometry of tomographic imaging systems, including CT, cone-beam CT (CBCT), and tomosynthesis systems. The invention enables image reconstruction in cases where it was not previously possible (e.g., custom-designed trajectories on robotic C-arms, or systems using uncalibrated geometries), and more broadly offers improved image quality (e.g., improved spatial resolution and reduced streak artifact) and robustness to patient motion (e.g., inherent compensation for rigid motion) in a manner that does not alter the patient setup or imaging workflow. The method provides a means for accurately estimating the complete geometric description of each projection acquired during a scan by simulating various poses of the x-ray source and detector to determine their unique, scan-specific positions relative to the patient, which is often unknown or inexactly known (e.g.

Abstract: An embodiment in accordance with the present invention provides a method for applying task-based performance predictors (measures of noise, spatial resolution, and detectability index) based on numerical observer models and approximations to the local noise and spatial resolution properties of the CBCT reconstruction process (e.g., penalized-likelihood iterative reconstruction). These predictions are then used to identify projections views (i.e., points that will constitute the scan trajectory) that maximize task performance, beginning with the projection view that maximizes detectability, proceeding to the next-best view, and continuing in an (arbitrarily constrained) orbit that can be physically realized on advanced robotic C-arm platforms.

Abstract: The present invention is directed to multiple aperture devices (MADs) for beam shaping in x-ray imaging. Two or more of these binary filters can be placed in an x-ray beam in series to permit a large number of x-ray fluence profiles. However, the relationship between particular MAD designs and the achievable fluence patterns is complex. The present invention includes mathematical and physical models that are used within an optimization framework to find optimal MAD designs. Specifically, given a set of target fluence patterns, the present invention finds, for example, a dual MAD design that is a “best fit” in generating the desired fluence patterns. This process provides a solution for both the design of MAD filters as well as the control actuation that is required (relative motion between MADs) that needs to be specified as part of the operation of a MAD-based fluence field modulation system.

Abstract: The present invention is directed to a method for enabling volumetric image reconstruction from unknown projection geometry of tomographic imaging systems, including CT, cone-beam CT (CBCT), and tomosynthesis systems. The invention enables image reconstruction in cases where it was not previously possible (e.g., custom-designed trajectories on robotic C-arms, or systems using uncalibrated geometries), and more broadly offers improved image quality (e.g., improved spatial resolution and reduced streak artifact) and robustness to patient motion (e.g., inherent compensation for rigid motion) in a manner that does not alter the patient setup or imaging workflow. The method provides a means for accurately estimating the complete geometric description of each projection acquired during a scan by simulating various poses of the x-ray source and detector to determine their unique, scan-specific positions relative to the patient, which is often unknown or inexactly known (e.g.

Abstract: A framework, comprising techniques, process(es), device(s), system(s), combinations thereof, or the like, to analyze propagation of information in prior-image-based reconstruction by decomposing the estimation into distinct components supported by a current data acquisition and by a prior image. Such decomposition can quantify contributions from prior data and current data as a spatial map and/or can trace specific features in an image to a source of at least some of such features.

Abstract: A method for processing an image of a series of images includes receiving first data representing a first previously reconstructed image and receiving second data representing a second image. A second image is reconstructed in accordance with the first data, the second data and a noise model. The noise model is a likelihood estimation. The second image is reconstructed in accordance with a penalty function. The penalty function is a roughness penalty function. The penalty function is updated by iteratively adjusting an image volume estimate. The penalty function is updated by iteratively adjusting a registration term. The penalty function is a prior image penalty function and the prior image penalty function and a registration term are jointly optimized. The penalty function is determined in accordance with a noise model. The function is a p-norm penalty function.

Abstract: An embodiment in accordance with the present invention provides a method for applying task-based performance predictors (measures of noise, spatial resolution, and detectability index) based on numerical observer models and approximations to the local noise and spatial resolution properties of the CBCT reconstruction process (e.g., penalized-likelihood iterative reconstruction). These predictions are then used to identify projections views (i.e., points that will constitute the scan trajectory) that maximize task performance, beginning with the projection view that maximizes detectability, proceeding to the next-best view, and continuing in an (arbitrarily constrained) orbit that can be physically realized on advanced robotic C-arm platforms.

Abstract: An imaging system for processing image data of an object containing a component. The imaging system includes an imaging device arranged to obtain image data and a processor. The processor is adapted to receive the image data from the imaging device, obtain a component model for the component, obtain an imaging device model for the imaging device, construct an unconstrained objective function based on the component model and the imaging device model, and construct a model of the object containing the component based on the unconstrained objective function and the image data, and a display device adapted to display an image for the object containing the component based on the model.

Abstract: A framework, comprising techniques, process(es), device(s), system(s), combinations thereof, or the like, to analyze propagation of information in prior-image-based reconstruction by decomposing the estimation into distinct components supported by a current data acquisition and by a prior image. Such decomposition can quantify contributions from prior data and current data as a spatial map and/or can trace specific features in an image to a source of at least some of such features.

Abstract: A method for processing an image of a series of images includes receiving first data representing a first previously reconstructed image and receiving second data representing a second image. A second image is reconstructed in accordance with the first data, the second data and a noise model. The noise model is a likelihood estimation. The second image is reconstructed in accordance with a penalty function. The penalty function is a roughness penalty function. The penalty function is updated by iteratively adjusting an image volume estimate. The penalty function is updated by iteratively adjusting a registration term. The penalty function is a prior image penalty function and the prior image penalty function and a registration term are jointly optimized. The penalty function is determined in accordance with a noise model. The function is a p-norm penalty function.

Abstract: An imaging system for processing image data of an object containing a component. The imaging system includes an imaging device arranged to obtain image data and a processor. The processor is adapted to receive the image data from the imaging device, obtain a component model for the component, obtain an imaging device model for the imaging device, construct an unconstrained objective function based on the component model and the imaging device model, and construct a model of the object containing the component based on the unconstrained objective function and the image data, and a display device adapted to display an image for the object containing the component based on the model.