Abstract: The present disclosure relates to training one or more neural networks for vascular vessel assessment using synthetic image data for which ground-truth data is known. In certain implementations, the synthetic image data may be based in part, or derived from, clinical image data for which ground-truth data is not known or available. Neural networks trained in this manner may be used to perform one or more of vessel segmentation, decalcification, Hounsfield unit scoring, and/or estimation of a hemodynamic parameter.

Abstract: The present disclosure relates to image reconstruction with favorable properties in terms of noise reduction, spatial resolution, detail preservation and computational complexity. The disclosed techniques may include some or all of: a first-pass reconstruction, a simplified datafit term, and/or a deep learning denoiser. In various implementations, the disclosed technique is portable to different CT platforms, such as by incorporating a first-pass reconstruction step.

Abstract: A method for characterizing anatomical features includes receiving scanned data and image data corresponding to a subject. The scanned data comprises sinogram data. The method further includes identifying a first region in an image of the image data corresponding to a region of interest. The method also includes determining a second region in the scanned data. The second region corresponds to the first region. The method further includes identifying a sinogram trace corresponding to the region of interest. The sinogram trace comprises sinogram data present within the second region. The method includes determining a data feature of the subject based on the sinogram trace and a deep learning network. The method also includes determining a diagnostic condition corresponding to a medical condition of the subject based on the data feature.

Abstract: A method for characterizing anatomical features includes receiving scanned data and image data corresponding to a subject. The scanned data comprises sinogram data. The method further includes identifying a first region in an image of the image data corresponding to a region of interest. The method also includes determining a second region in the scanned data. The second region corresponds to the first region. The method further includes identifying a sinogram trace corresponding to the region of interest. The sinogram trace comprises sinogram data present within the second region. The method includes determining a data feature of the subject based on the sinogram trace and a deep learning network. The method also includes determining a diagnostic condition corresponding to a medical condition of the subject based on the data feature.

Abstract: An X-ray filter assembly is disclosed having a stack of X-ray attenuating sheets that are angled so as to have a focus point. When implemented in an imaging system, the focus point of the filter assembly is spatially offset (e.g., behind) the X-ray emission location. The filter assembly may be used (e.g., translated, rotated, and so forth) to adjust the intensity profile of the X-rays seen in an imaging volume.

Abstract: The present approaches relate to frequency-split iterative reconstruction approaches. In some embodiment, such approaches provide for the combination of the low frequency components of an analytical reconstruction (e.g., a filtered back projection) and the high frequency components of an iterative reconstruction. In certain embodiments, frequency-split iterative reconstruction is used for generating region of interest images.

Abstract: According to some embodiments, system and methods are provided comprising determining one or more image locations at which motion occurred within an image volume of an object containing movable anatomical features prior to segmenting the movable anatomical features; estimating motion at each of the one or more image locations; correcting one or more motion artifacts in the image volume at each of the one or more image locations, where motion was estimated resulting in the generation of a final motion compensated image; and segmenting one or more features of interest in the final motion compensated image. Numerous other aspects are provided.

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: The present approach provides a non-invasive methodology for estimation of coronary flow and/or fractional flow reserve. In certain implementations, various approaches for personalizing blood flow models of the coronary vasculature are described. The described personalization approaches involve patient-specific measurements and do not assume or rely on the resting coronary flow being proportional to myocardial mass. Consequently, there are fewer limitations in using these approaches to obtain coronary flow and/or fractional flow reserve estimates non-invasively.

Abstract: According to some embodiments, system and methods are provided comprising determining one or more image locations at which motion occurred within an image volume of an object containing movable anatomical features prior to segmenting the movable anatomical features; estimating motion at each of the one or more image locations; correcting one or more motion artifacts in the image volume at each of the one or more image locations, where motion was estimated resulting in the generation of a final motion compensated image; and segmenting one or more features of interest in the final motion compensated image. Numerous other aspects are provided.

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: 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: An X-ray filter assembly is disclosed having a stack of X-ray attenuating sheets that are angled so as to have a focus point. When implemented in an imaging system, the focus point of the filter assembly is spatially offset (e.g., behind) the X-ray emission location. The filter assembly may be used (e.g., translated, rotated, and so forth) to adjust the intensity profile of the X-rays seen in an imaging volume.

Abstract: An imaging system includes a computed tomography (CT) acquisition unit and a processing unit. The CT acquisition unit includes an X-ray source and a CT detector configured to collect CT imaging data of an object to be imaged. The X-ray source and CT detector are configured to be rotated about the object to be imaged and to collect a series of views of the object as the X-ray source and CT detector rotate about the object to be imaged. The processing unit is operably coupled to the CT acquisition unit and configured to control the CT acquisition unit to vary a view duration for the views of the series. The view duration for a particular view defines an imaging information acquisition period for the particular view, wherein the series of views includes a first group of views having a first view duration and a second group of views having a second view duration that is different than the first view duration.

Abstract: An imaging system is provided. The imaging system includes a rotating gantry. An x-ray source is mounted to the gantry. The system also includes a plurality of interchangeable x-ray detector modules is mounted to the gantry, opposite the x-ray source. The plurality of interchangeable detector modules includes a first detector module mounted at a first distance from the x-ray source and a second detector module mounted at a second distance from the x-ray source. The first distance is different from the second distance.

Abstract: The present approaches relate to frequency-split iterative reconstruction approaches. In some embodiment, such approaches provide for the combination of the low frequency components of an analytical reconstruction (e.g., a filtered back projection) and the high frequency components of an iterative reconstruction. In certain embodiments, frequency-split iterative reconstruction is used for generating region of interest images.

Abstract: Various methods and systems for generating a computed tomography image in real-time are provided. In one embodiment, a method for imaging comprises acquiring x-ray projection data; calibrating the x-ray projection data; generating at least two basis image volumes by reconstructing the calibrated x-ray projection data, each of the at least two basis image volumes including different centerviews and a temporal width corresponding to an x-ray source rotation between 180 degrees and 360 degrees; and generating a final image volume by Fourier blending the at least two basis image volumes based on a selected temporal window width. In this way, a user may scroll between Fourier-blended images of varying durations of temporal window in real-time to select an optimal image for review without a reconstruction of calibrated x-ray projection data for each image.

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: An imaging system includes a computed tomography (CT) acquisition unit and a processing unit. The CT acquisition unit includes an X-ray source and a CT detector configured to collect CT imaging data of an object to be imaged. The X-ray source and CT detector are configured to be rotated about the object to be imaged and to collect a series of views of the object as the X-ray source and CT detector rotate about the object to be imaged. The processing unit is operably coupled to the CT acquisition unit and configured to control the CT acquisition unit to vary a view duration for the views of the series. The view duration for a particular view defines an imaging information acquisition period for the particular view, wherein the series of views includes a first group of views having a first view duration and a second group of views having a second view duration that is different than the first view duration.

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.