Abstract: A method for reducing noise in a medical diagnostic image includes acquiring an initial three-dimensional (3D) volume of projection data, generating a projection space noise estimate using the 3D volume of projection data, generating an initial 3D volume of image data using the 3D volume of projection data, generating an image space noise estimate using the 3D volume of image data, generating a noise projection estimate using the projection space noise estimate and the image space noise estimate, and reconstructing an image using the generated noise estimate. A system and non-transitory computer readable medium are also described.

Abstract: An imaging system includes a computer programmed to estimate noise in computed tomography (CT) imaging data, correlate the noise estimation with neighboring CT imaging data to generate a weighting estimation based on the correlation, de-noise the CT imaging data based on the noise estimation and on the weighting, and reconstruct an image using the de-noised CT imaging data.

Abstract: An imaging system includes a computer programmed to reconstruct original CT projection data, estimate noise in image space, forward project the image noise estimate to generate an initial projection noise estimate, modify the initial projection noise estimate using a statistical property of noise in projection space, remove noise in the original CT projection data by subtracting the modified noise estimate therefrom to generate noise-removed projection data, and reconstruct a final image based on the noise-removed projection data.

Abstract: An imaging system includes an x-ray source, a detector, a data acquisition system (DAS) operably connected to the detector, and a computer operably connected to the DAS. The computer is programmed to obtain CT scan data with two or more incident energy spectra, decompose the obtained CT scan data into projection CT data of a first basis material and a second basis material, generate a first basis material image and a second basis material image using the decomposed projection CT data, generate a first monochromatic image from the first basis material image and the second basis material image at a first energy that is selected based on an amount of correlated noise at the first energy, noise-reduce the first monochromatic image to generate a noise-reduced first monochromatic image, and generate a final monochromatic image based at least on the noise-reduced first monochromatic image.

Abstract: Systems and methods for multichannel noise reduce are provided. One method includes acquiring a multichannel signal, obtaining a noise correlation between a plurality of channels of the multichannel signal, and obtaining a signal characteristic in each of the plurality of channels. The method also includes removing signal noise based on (i) the correlated noise and (ii) at least one of an uncorrelated noise in each channel or the obtained signal characteristic in each channel.

Abstract: A method for reducing noise in a medical diagnostic image includes acquiring an initial three-dimensional (3D) volume of projection data, generating a projection space noise estimate using the 3D volume of projection data, generating an initial 3D volume of image data using the 3D volume of projection data, generating an image space noise estimate using the 3D volume of image data, generating a noise projection estimate using the projection space noise estimate and the image space noise estimate, and reconstructing an image using the generated noise estimate. A system and non-transitory computer readable medium are also described.

Abstract: A system and method for material decomposition optimization in the image domain include a non-transitory computer readable medium has stored thereon a sequence of instructions which, when executed by a computer, causes the computer to access a reconstructed basis material image. For a first voxel of the reconstructed basis material image, the instructions also cause the computer to optimize a concentration of a pair of materials (a,b) in the first voxel exclusively in the image domain and based on a first probability based on random perturbations and a second probability based on random perturbations. The optimization is further based on a third probability based on known materials and a fourth probability based on concentrations of the pair of materials in a pair of voxels neighboring the first voxel.

Abstract: A CT system includes a gantry, an x-ray source, a detector, and a grating collimator that includes alternating first and second materials. The system includes a controller configured to emit a first beam of x-rays from a first focal spot and to a first detector pixel, wherein the first beam of x-rays passes along a ray and through one of the first materials of the grating collimator, and subsequently emit a second beam of x-rays from a second focal spot and to the first detector pixel, wherein the second beam of x-rays passes substantially along the ray and through one of the second materials of the grating collimator. The system includes a computer programmed to generate first and second kVp image datasets using data acquired from the first beam and second beams of x-rays, and reconstruct a basis material image of the object.

Abstract: A CT system includes a generator configured to energize an x-ray source to a first kilovoltage (kVp) and to a second kVp, and a computer that is programmed to acquire a first view dataset with the x-ray source energized to the first kVp and a second view dataset with the x-ray source energized to the second kVp, generate a base correction image using the first view dataset and the second view dataset, and reconstruct a pair of base material images from the first view dataset and from the second view dataset. The computer is also programmed to estimate artifact correlation in the pair of base material images using the base correction image, generate a pair of final base material images and a final monochromatic image, and correct one of the pair of final base material images and the final monochromatic image at a keV value using the estimated artifact correlation.

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: The subject matter disclosed herein relates to X-ray imaging systems, and more specifically, to multi-energy computed tomography (CT) X-ray imaging systems. In an embodiment, a multi-energy computed tomography (CT) imaging system includes an X-ray source that emits X-rays upon the application of a low stable bias, a high stable bias, and transitional biases between the low stable bias and the high stable bias. The imaging system also includes an X-ray detector configured to produce an electrical signal corresponding to the intensity of the X-rays emitted by the X-ray source that reach the X-ray detector. The imaging system also includes data processing circuitry configured to acquire a first set of data corresponding to the electrical signal produced by the X-ray detector only when the low stable bias or the high stable bias is applied to the X-ray source. The imaging system also includes a processor configured to process the first set of acquired data and construct one or more multi-energy CT images.

Abstract: Systems and methods for multichannel noise reduce are provided. One method includes acquiring a multichannel signal, obtaining a noise correlation between a plurality of channels of the multichannel signal, and obtaining a signal characteristic in each of the plurality of channels. The method also includes removing signal noise based on (i) the correlated noise and (ii) at least one of an uncorrelated noise in each channel or the obtained signal characteristic in each channel.

Abstract: A CT scanner comprising a dynamic collimator disposed near an x-ray source and a controller configured to rotate the x-ray source about a subject, wherein imaging data is acquired from a single rotation of the x-ray source, the single rotation being divided into a first half-scan and a second half-scan. The controller is further configured to position the dynamic collimator after acquiring image data from one of the first half-scan and the second half-scan and simultaneous to commencement of acquiring image data from the other of the first half-scan and the second half-scan to obstruct a central portion of an x-ray beam emitted by the x-ray source during one of the first half-scan and the second half-scan. The CT scanner is further configured to reconstruct a CT image using the first set of imaging data and the second set of imaging data.

Abstract: A CT scanner comprising a dynamic collimator disposed near an x-ray source and a controller configured to rotate the x-ray source about a subject, wherein imaging data is acquired from a single rotation of the x-ray source, the single rotation being divided into a first half-scan and a second half-scan. The controller is further configured to position the dynamic collimator after acquiring image data from one of the first half-scan and the second half-scan and simultaneous to commencement of acquiring image data from the other of the first half-scan and the second half-scan to obstruct a central portion of an x-ray beam emitted by the x-ray source during one of the first half-scan and the second half-scan. The CT scanner is further configured to reconstruct a CT image using the first set of imaging data and the second set of imaging data.

Abstract: A system and method for material decomposition optimization in the image domain include a non-transitory computer readable medium has stored thereon a sequence of instructions which, when executed by a computer, causes the computer to access a reconstructed basis material image. For a first voxel of the reconstructed basis material image, the instructions also cause the computer to optimize a concentration of a pair of materials (a,b) in the first voxel exclusively in the image domain and based on a first probability based on random perturbations and a second probability based on random perturbations. The optimization is further based on a third probability based on known materials and a fourth probability based on concentrations of the pair of materials in a pair of voxels neighboring the first voxel.

Abstract: A CT scanner comprising a dynamic collimator disposed near an x-ray source and a controller configured to rotate the x-ray source about a subject, wherein imaging data is acquired from a single rotation of the x-ray source, the single rotation being divided into a first half-scan and a second half-scan. The controller is further configured to position the dynamic collimator after acquiring image data from one of the first half-scan and the second half-scan and simultaneous to commencement of acquiring image data from the other of the first half-scan and the second half-scan to obstruct a central portion of an x-ray beam emitted by the x-ray source during one of the first half-scan and the second half-scan. The CT scanner is further configured to reconstruct a CT image using the first set of imaging data and the second set of imaging data.

Abstract: A method for reconstructing an image using an imaging apparatus that includes a radiation source, a detector array, and a computer. The method includes performing a helical scan of an object at a selected helical pitch using the radiation source and detector array to obtain image data, and reconstructing an image of the object utilizing the computer programmed to perform a hybrid cone beam image reconstruction having ray-wise 3D weighting, wherein the weighting is dependent upon both helical pitch and z-distance.

Abstract: An imaging system includes an x-ray source, a detector, a data acquisition system (DAS) operably connected to the detector, and a computer operably connected to the DAS. The computer is programmed to obtain CT scan data with two or more incident energy spectra, decompose the obtained CT scan data into projection CT data of a first basis material and a second basis material, generate a first basis material image and a second basis material image using the decomposed projection CT data, generate a first monochromatic image from the first basis material image and the second basis material image at a first energy that is selected based on an amount of correlated noise at the first energy, noise-reduce the first monochromatic image to generate a noise-reduced first monochromatic image, and generate a final monochromatic image based at least on the noise-reduced first monochromatic image.

Abstract: A CT system includes a generator configured to energize an x-ray source to a first kilovoltage (kVp) and to a second kVp, and a computer that is programmed to acquire a first view dataset with the x-ray source energized to the first kVp and a second view dataset with the x-ray source energized to the second kVp, generate a base correction image using the first view dataset and the second view dataset, and reconstruct a pair of base material images from the first view dataset and from the second view dataset. The computer is also programmed to estimate artifact correlation in the pair of base material images using the base correction image, generate a pair of final base material images and a final monochromatic image, and correct one of the pair of final base material images and the final monochromatic image at a keV value using the estimated artifact correlation.

Abstract: A method for reconstructing an image using an imaging apparatus that includes a radiation source, a detector array, and a computer. The method includes performing a helical scan of an object at a selected helical pitch using the radiation source and detector array to obtain image data, and reconstructing an image of the object utilizing the computer programmed to perform a hybrid cone beam image reconstruction having ray-wise 3D weighting, wherein the weighting is dependent upon both helical pitch and z-distance.