Abstract: A system includes a reconstructor (314) configured to reconstruct cone beam projection data to generate cone beam artifact corrected short scan cone beam volumetric image data. A method includes reconstructing, with a reconstructor, cone beam projection data to generate cone beam artifact corrected short scan cone beam volumetric image data. A computer-readable storage medium storing computer executable instructions which when executed by a processor of a computer cause the processor to: reconstruct cone beam projection data to generate cone beam artifact corrected short scan cone beam volumetric image data.

Abstract: A mechanism for generating a partially denoised image. A residual noise image, obtained by processing an image using a convolutional neural network, is weighted. The blending or combination of the weighted residual noise image and the (original) image generates the partially denoised image.

Abstract: An imaging system (302) includes an X-ray radiation source (312) configured to emit radiation that traverses an examination region, a detector array (314) configured to detect radiation that traverses an examination region and generate a signal indicative thereof, wherein the detected radiation is for a 3-D pre-scan, and a reconstructor (316) configured to reconstruct the signal to generate a 2-D pre-scan projection image. The imaging system further includes a console (318) wherein a processor thereof is configured to execute 3-D volume planning instructions (328) in memory to display the 2-D pre-scan projection image (402, 602, 802, 1002) and a scan plan or bounding box (404, 604, 804, 1004) for planning a 3-D volume scan of a region/tissue of interest based on a selected protocol for a 3-D volume scan of a region/tissue of interest being planned and receive an input confirming or adjusting the scan plan box to create a 3-D volume scan plan for the 3-D volume scan of the region/tissue of interest.

Abstract: A method for use in a material decomposition procedure applied to dual-energy CT projection data. Material decomposition is often done using pre-computed lookup tables (LUTs) for mapping input projection data, acquired with particular X-ray source parameters, to material data values. However, the X-ray source parameters can vary over the course of a scan, making the results inaccurate. Embodiments are based on determining in advance a plurality of sets of basis LUTs for each of a plurality of different possible ranges of values over which the X-ray source parameter may vary during a scan. The basis LUTs in each set are devised as being LUTs which represent the majority contribution to the overall material decomposition function for the time-varying energy spectrum.

Abstract: A system (116) includes an unlogger (202) configured to unlog logged data, to produce unlogged clipped data. The logged data includes attenuation line integrals and clipping-induced bias. The system further includes a mean estimator (204) configured to estimate a mean value of the unlogged clipped data. The system further includes a correction determiner (206) configured to determine correction to the clipping-induced bias based on the estimated mean value of the unlogged clipped data. The system further includes an adder (210) configured to correct the logged data with the correction to produce corrected logged data.

Abstract: A method is provided for processing medical images, the method including receiving a first image and a second image different from the first image, where the second image is of the same subject matter as the first image. The method further includes identifying a plurality of anatomical structures in the first image and defining a plurality of image segments in the second image based N on locations of the anatomical structures identified in the first image. The method then applies a processing routine associated with a first anatomical structure to the first image segment in the second image and a processing routine associated with a second anatomical structure to the second image segment in the second image. Also provided is an imaging system for implementing the described method and a non-transitory computer readable medium storing a program for processing medical images.

Abstract: The present invention relates to a method and a cone beam computed tomography apparatus for reducing artefacts in an image acquired with the cone beam computed tomography apparatus using a second pass artefact reduction method. Projection data of an object are acquired, wherein the projection data comprises a first subset of data to be used for reconstruction of a first image, and a second subset of data comprising projection data not to be used for the construction of the first image, wherein the second subset of data comprises projection data not comprised in the first subset of data. A first and a second image are reconstructed using the first and the second subset of data, respectively. A second pass artefact reduction method is performed using the second image as input image of the second pass artefact reduction method, thereby reducing artefacts in the first image.

Abstract: One embodiment of the present disclosure may provide a method for training and tuning a neural network model, including: adding simulated noise to an initial image of an object to generate a noisy image (601, 603), the simulated noise taking the same form as natural noise in the initial image; training a neural network model on the noisy image using the initial image as ground truth (605), wherein in the neural network model is trained on the noisy work model a tuning variable is extracted or generated, the tuning variable defining an amount of noise removed during use (607); identifying a first value for the tuning variable that minimizes a training cost function for the tuning variable is identified or for the initial image; and assigning a second value for the tuning variable (611), the second value different than the first value, wherein the neural network model identifies more noise in the noisy image when using the second value than when using the first value.

Abstract: A system includes a reconstructor (314) configured to reconstruct cone beam projection data to generate cone beam artifact corrected short scan cone beam volumetric image data. A method includes reconstructing, with a reconstructor, cone beam projection data to generate cone beam artifact corrected short scan cone beam volumetric image data. A computer-readable storage medium storing computer executable instructions which when executed by a processor of a computer cause the processor to: reconstruct cone beam projection data to generate cone beam artifact corrected short scan cone beam volumetric image data.

Abstract: An imaging system (302) includes an X-ray radiation source (312) configured to emit radiation that traverses an examination region, a detector array (314) configured to detect radiation that traverses an examination region and generate a signal indicative thereof, wherein the detected radiation is for a 3-D pre-scan, and a reconstructor (316) configured to reconstruct the signal to generate a 2-D pre-scan projection image. The imaging system further includes a console (318) wherein a processor thereof is configured to execute 3-D volume planning instructions (328) in memory to display the 2-D pre-scan projection image (402, 602, 802, 1002) and a scan plan or bounding box (404, 604, 804, 1004) for planning a 3-D volume scan of a region/tissue of interest based on a selected protocol for a 3-D volume scan of a region/tissue of interest being planned and receive an input confirming or adjusting the scan plan box to create a 3-D volume scan plan for the 3-D volume scan of the region/tissue of interest.

Abstract: An imaging system (702) includes a reconstructor (716) configured to reconstruct obtained cone beam projection data with a voxel-dependent redundancy weighting such that low frequency components of the cone beam projection data are reconstructed with more redundant data than high frequency components of the cone beam projection data to produce volumetric image data. A method includes reconstructing obtained cone beam projection data with a voxel-dependent redundancy weighting such that low frequency components are reconstructed with more redundant data than high frequency components to produce volumetric image data.

Abstract: A medical imaging system (200) includes a masking unit (234), an image registration unit (238), a motion estimator (240) and a motion compensating reconstructor (244). The masking unit constructs a mask for each reconstructed volumetric phase image of a plurality of reconstructed volumetric phase images that masks portions of a corresponding image external to an anatomical model fitted to a segmented at least one anatomical structure, 5 wherein the plurality of reconstructed volumetric phase images include a target phase and a plurality of temporal neighboring phases reconstructed from projection data. The image registration unit registers the masked reconstructed volumetric phase images. The motion estimator estimates motion between the target phase and the plurality of temporal neighboring phases according to the model based on the registered masked reconstructed 10 volumetric phase images.

Abstract: An imaging system includes a rotating gantry with a bore, and an X-ray radiation source supported by the rotating gantry, which rotates around the bore and emit X-ray radiation that traverses at least a portion of the bore. A detector array supported by the rotating gantry, located opposite the X-ray radiation source, detects the X-ray radiation having traversed an object located within the bore and generate projection data indicative of the detected X-ray radiation, wherein the projection data comprises a sinogram. A processor estimates a portion of the object truncated in the sinogram by fitting a curve to data sampled from a plurality of views of the object in the sinogram adjacent to a set of truncated views of the object in the sinogram, and reconstructs an image of the object based on the estimated portion of the object truncated and the generated projection data.

Abstract: An imaging method includes obtaining projection data for a helical scan of a subject. The method further includes reconstructing, for a particular time and image slice location of interest, a first temporal motion state image at an earlier time on the detector array and offset from the central row in a first direction with projection data from a first to subset of detector rows, and reconstructing, for the particular time and image slice location, a second temporal motion state image at a later time on the detector array and offset from the central row in a second direction with projection data from a second different subset of detector rows. The method further includes estimating a distortion vector field between the first and second temporal motion state images, and constructing motion compensated volu-metric image data with a motion compensated reconstruction algorithm using the distortion vector field to compensate for arbitrary motion.

Abstract: Present multi-spectral CT approaches are able to cancel the noise from the combined (mono-energy) image. However, medical professionals also find it useful to consult the basis images which are combined (summed) form the mono image, because they can provide useful extra diagnostic information. However, denoising of the basis images can lead to a “jagged” appearance of edges in the denoised basis images, inconveniently requiring further image processing steps to take place before the basis images can be clearly read. Accordingly, there is provided an apparatus (30) for simultaneous edge noise reduction. The apparatus comprises a processor (32). The processor is configured to receive first (s0) and second (p0) input image data, and to receive first (s) and second (p) denoised input image data. The first and second input image data contains noise which is anti-correlated between the first and the second input image data.

Abstract: A reconstruction system includes a decomposer (204) configured to decompose at least two sets of projection data generated via kVp switching between at least two radiation source voltages. Each set corresponds to a different one of the at least two radiation source voltages. The system further includes a spectral channel (206) configured to process the at least two sets of projection data and generate spectral image data. The system further includes a non-spectral channel (208) configured to process the at least two sets of projection data and generate non-spectral image data for a predetermined reference kVp.

Abstract: A system (116) includes an unlogger (202) configured to unlog logged data, to produce unlogged clipped data. The logged data includes attenuation line integrals and clipping- induced bias. The system further includes a mean estimator (204) configured to estimate a meanvalue of the unlogged clipped data. The system further includes a correction determiner (206) configured to determine a correction to the clipping-induced bias based on the estimated mean value of the unlogged clipped data. The system further includes an adder (210) configured to correct the logged data with the correction to produce corrected logged data.

Abstract: A system (300) includes input/output configured to receive line integrals from a contrast enhanced spectral scan by an imaging system. The system further includes (300) a processor (326) configured to: decompose (334) the line integrals into at least Compton scatter and a photo-electric effect line integrals; reconstruct the Compton scatter and a photo-electric effect line integrals to generate spectral image data, including at least Compton scatter and photo-electric effect images; de-noise (332) the Compton scatter and photo-electric effect images; identify (402) residual iodine voxels in the de-noised Compton scatter and the photo-electric effect images corresponding to residual iodine artifact; and produce a virtual non-contrast image using the identified residual iodine voxels.

Abstract: An imaging system (400) includes a radiation source (408) configured to emit X-ray radiation, a detector array (410) configured to detected X-ray radiation and generate projection data indicative thereof, and a first processing chain (418) configured to reconstruct the projection data and generate a noise only image. A method includes receiving projection data produced by an imaging system and processing the projection data with a first processing chain configured to reconstruct the projection data and generate a noise only image. A processor is configured to: scan an object or subject with an x-ray imaging system and generating projection data, process the projection data with a first processing chain configured to reconstruct the projection data and generate a noise only image, process the projection data with a second processing chain configured to reconstruct the projection data and generate a structure image, and de-noise the structure image based on the noise only image.

Abstract: A system includes a single backprojector (120), which includes a single geometry calculator (204), at least one weight calculator (206), and a plurality of data interpolators (208). The single geometry calculator is configured to process scan parameters of a single computed tomography scan to generate geometry values only once for each voxel position in a volumetric image data matrix. The at least one weight calculator is configured to process the scan parameters of the single computed tomography scan and the geometry values to generate weight values for each voxel position in the volumetric image data matrix. Each of the plurality of data interpolators is configured to process, using the weight values and the same geometry values, a respective different type of projection data produced from the same single computed tomography scan to generate volumetric image data based on the volumetric image data matrix and corresponding to the respective different type of projection data.