Abstract: Systems and methods are provided for synthesizing information from multiple image series of different kernels into a single image series, and also for converting a single baseline image series of a kernel reconstructed by a CT scanner to image series of various other kernels, using deep-learning based methods. For multi-kernel synthesis, a single set of images with desired high spatial resolution and low image noise can be synthesized from multiple image series of different kernels. The synthesized kernel is sufficient for a wide variety of clinical tasks, even in circumstances that would otherwise require many separate image sets. Kernel conversion may be configured to generate images with arbitrary reconstruction kernels from a single baseline kernel. This would reduce the burden on the CT scanner and the archival system, and greatly simplify the clinical workflow.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A system and method for acquiring an image of a region of interest (ROI) of subject using a computed tomography (CT) system includes a) performing a scout scan of the subject using the CT system to yield scout data related to the ROI and b) determining an initial contrast volume form at least the scout data. The method also includes c) prescribing a scanning protocol to be implemented using the computed tomography system to image the ROI and d) determining a size of the subject about the ROI. The method further includes e) determining a computed tomography dose related to volume (CTDIvol) based on at least the size determined at step d) and f) adjusting the scanning protocol prescribed in step b) to match at least one of a desired radiation dose and a relative intravenous (IV) contrast dose to a reference CTDIvol. The method includes g) acquiring imaging data from the ROI using the CT system by using the adjusted scanning protocol.

Abstract: A system and method is provided for estimating the local noise of CT images and denoising the images using a modified non-local means (NLM) algorithm that is adaptive to local variations of noise levels. A strategy for efficiently estimating the local noise of CT images is also described.

Abstract: Projection data acquired with an x-ray CT system is filtered using a bilateral filter to reduce image noise and enable the acquisition at lower x-ray dose without the loss of image diagnostic quality. The bilateral filtering is performed before image reconstruction by producing a noise equivalent data set from the acquired projection data and then converting the bilateral filtered values back to a projection data set suitable for image reconstruction.

Abstract: A method for CT imaging that utilizes an automatic tube potential selection for individual subjects and diagnostic tasks. The method quantifies the relative radiation dose of different tube potentials for achieving a specific image quality. This allows the selection of a tube potential that provides a reduced radiation dose while still providing CT images of a sufficient quality.

Abstract: A method for CT imaging that utilizes an automatic tube potential selection for individual subjects and diagnostic tasks. The method quantifies the relative radiation dose of different tube potentials for achieving a specific image quality. This allows the selection of a tube potential that provides a reduced radiation dose while still providing CT images of a sufficient quality.

Abstract: A method for CT imaging that utilizes an automatic tube potential selection for individual subjects and diagnostic tasks. The method quantifies the relative radiation dose of different tube potentials for achieving a specific image quality. This allows the selection of a tube potential that provides a reduced radiation dose while still providing CT images of a sufficient quality.

Abstract: A system and method is provided for estimating the local noise of CT images and denoising the images using a modified non-local means (NLM) algorithm that is adaptive to local variations of noise levels. A strategy for efficiently estimating the local noise of CT images is also described.

Abstract: A system and method for reconstructing an image acquired by delivering an irradiating dose of radiation to a subject includes acquiring imaging data using a dose of irradiating radiation and selecting at least one of a plurality of mechanisms for reducing the dose that could be delivered to the subject to acquire additional imaging data. Noise is inserted into the imaging data to simulate the at least one of the plurality of mechanisms for reducing the dose that could be applied to acquire the additional imaging data to thereby generate simulated imaging data at a reduced dose of irradiating radiation. A simulated reduced dose image is reconstructed from the simulated imaging data. A method is provided for utilizing a non-local means filter adapted using a map of local noise to produce denoised medical imaging data reflecting reduced local nose levels from those in originally-acquired medical imaging data.

Abstract: A method for creating an energy series of images acquired using a multi-energy computed tomography (CT) imaging system having a plurality of energy bins includes acquiring, with the multi-energy CT imaging system, a series of energy data sets, where each energy data set is associated with at least one of the energy bins. The method includes producing a conglomerate image using at least a plurality of the energy data sets and, using the conglomerate image, reconstructing an energy series of images, each image in the energy series of images corresponding to at least one of the energy data sets.

Abstract: A system and method for acquiring an image of a region of interest (ROI) of subject using a computed tomography (CT) system includes a) performing a scout scan of the subject using the CT system to yield scout data related to the ROI and b) determining an initial contrast volume form at least the scout data. The method also includes c) prescribing a scanning protocol to be implemented using the computed tomography system to image the ROI and d) determining a size of the subject about the ROI. The method further includes e) determining a computed tomography dose related to volume (CTDIvol) based on at least the size determined at step d) and f) adjusting the scanning protocol prescribed in step b) to match at least one of a desired radiation dose and a relative intravenous (IV) contrast dose to a reference CTDIvol. The method includes g) acquiring imaging data from the ROI using the CT system by using the adjusted scanning protocol.

Abstract: A method for CT imaging that utilizes an automatic tube potential selection for individual subjects and diagnostic tasks. The method quantifies the relative radiation dose of different tube potentials for achieving a specific image quality. This allows the selection of a tube potential that provides a reduced radiation dose while still providing CT images of a sufficient quality.

Abstract: Projection data acquired with an x-ray CT system is filtered using a bilateral filter to reduce image noise and enable the acquisition at lower x-ray dose without the loss of image diagnostic quality. The bilateral filtering is performed before image reconstruction by producing a noise equivalent data set from the acquired projection data and then converting the bilateral filtered values back to a projection data set suitable for image reconstruction.