Abstract: A method includes re-sampling current image data representing a reference motion state into a plurality of different groups, each group corresponding to a different motion state of moving tissue of interest, forward projecting each of the plurality of groups, generating a plurality of groups of forward projected data, each group of forward projected data corresponding to a group of the re-sampled current image data, determining update projection data based on a comparison between the forward projected data and the measured projection data, grouping the update projection data into a plurality of groups, each group corresponding to a different motion state of the moving tissue of interest, back projecting each of the plurality of groups, generating a plurality of groups of update image data, re-sampling each group of update image data to the reference motion state of the current image, and generating new current image data based on the current image data and the re-sampled update image data.

Abstract: Image processing methods and related apparatuses (SEG,UV). The apparatuses (SEG,UV) operate to utilize noise signal information in images (IM). According to one aspect, apparatus (SEG) uses the noise information (FX) to control a model based segmentation. According to a further aspect, apparatus (UV) operates, based on the noise information (FX), to visualize the uncertainty of image information that resides at edge portions of the or an image (IM).

Abstract: A method includes obtaining a dark-field signal generated from a dark-field CT scan of an object, wherein the dark-field CT scan is at least a 360 degree scan. The method further includes weighting the dark-field signal. The method further includes performing a cone beam reconstruction of the weighted dark-field signal over the 360 degree scan, thereby generating volumetric image data. For an axial cone-beam CT scan, in one non-limiting instance, the cone-beam reconstruction is a full scan FDK cone beam reconstruction. For a helical cone-beam CT scan, in one non-limiting instance, the dark-field signal is rebinned to wedge geometry and the cone-beam reconstruction is a full scan aperture weighted wedge reconstruction. For a helical cone-beam CT scan, in another non-limiting instance, the dark-field signal is rebinned to wedge geometry and the cone-beam reconstruction is a full scan angular weighted wedge reconstruction.

Abstract: A signal processing apparatus and a related method. In particular, the apparatus includes a novel image reconstructor to reconstruct cross sectional images of a specimen from interferometric projection data (m). The reconstructor (RECON) is based on a new forward model that accounts for cross-talk of a phase contrast signal into a dark field signal.

Abstract: The present invention relates to an imaging apparatus and a corresponding imaging method.

Abstract: Described herein are technologies related to an implementation of a thermal management scheme in a device. Particularly, a look up table or LUT is configured to include a data set of information (e.g., user-profile data, network-profile data) and a corresponding recommended thermal throttling mode. During regular device operation, conditions internal/external to the device is detected and the corresponding thermal throttling mode (from the LUT) is applied. In certain implementations, optimization algorithms are used in place of the LUT.

Abstract: A method and a related system (IMA) for reconstructing an image of an electron density in a subject PAT. An x-ray radiation imager is used to expose the subject PAT to radiation to receive projection data. The reconstruction method combines projection data from two channels, namely Compton scatter based attenuation data pC and phase shift data pd?.

Abstract: This application describes an approach to filter, solely in the projection domain, correlated noise from (or de-noise) spectral/multi-energy projection data. As described herein, this can be achieved based at least on variances of the basis material line integrals and a covariance there between, based on multiple correlation coefficients and hyper-planes that describe the noise correlation between different basis material line integrals, and/or otherwise.

Abstract: The invention relates to an image generation apparatus (1) for generating an image of an object. A reconstruction unit (10) reconstructs the image based on provided measured projection values such that costs defined by a cost function are reduced, wherein the cost function depends on differences between calculated projection values, which have been determined by simulating a forward projection through the image, and the provided measured projection values, and wherein a degree of dependence of the cost function on a respective difference depends on the respective difference. This can allow for a consideration of a degree of disturbance of the measured projection values by motion and/or by an incomplete illumination of the object during the reconstruction process, which can lead to a reconstruction of an image having an improved image quality.

Abstract: A method includes obtaining projection data from a scan of a moving structure of interest. The method further includes reconstructing the projection data, generating first image data. The method further includes identifying a sub-set of the projection. The method further includes reconstructing the sub-set projection data, generating second image data. The method further includes identifying a region in which the moving structure of interest is located based on the first image data. The method further includes identifying a location of the moving structure of interest in the identified region based on the second image data.

Abstract: A method and related apparatus (116) for iterative reconstruction of a volume. A regularization parameter (?) of an iterative update function is spatially adapted and normalized in respect to a region of interest ROI in the volume. The method allows achieving essentially uniform noise distribution across the reconstructed volume.

Abstract: A beam hardening correction method, a related calibration method for tomographic image data and a related apparatus. The tomographic image data includes attenuation data (f) and phase gradient data (g) and/or small angle scattering data (h). A correction value is computed from the attenuation data (f) by applying a function (q) to the attenuation data (f). The correction value is combined (S445) with the phase gradient data (g) or with the small angle scattering data (h).

Abstract: A method and related apparatus (116) for iterative reconstruction of a volume. A regularization parameter (?) of an iterative update function is spatially adapted and normalized in respect to a region of interest ROI in the volume. The method allows achieving essentially uniform noise distribution across the reconstructed volume.

Abstract: A method and a related system (IMA) for reconstructing an image of an electron density in a subject PAT. An x-ray radiation imager is used to expose the subject PAT to radiation to receive projection data. The reconstruction method combines projection data from two channels, namely Compton scatter based attenuation data pC and phase shift data pd?.

Abstract: A method includes re-sampling current image data representing a reference motion state into a plurality of different groups, each group corresponding to a different motion state of moving tissue of interest, forward projecting each of the plurality of groups, generating a plurality of groups of forward projected data, each group of forward projected data corresponding to a group of the re-sampled current image data, determining update projection data based on a comparison between the forward projected data and the measured projection data, grouping the update projection data into a plurality of groups, each group corresponding to a different motion state of the moving tissue of interest, back projecting each of the plurality of groups, generating a plurality of groups of update image data, re-sampling each group of update image data to the reference motion state of the current image, and generating new current image data based on the current image data and the re-sampled update image data.

Abstract: A method includes receiving at least two sets of noisy basis material line integrals, each set corresponding to a different basis material and filtering the at least two sets of noisy basis material line integrals with an anti-correlation filter that at least includes a regularization term with balancing regularization factors, thereby producing de-noised basis material line integrals. An imaging system (100) includes a projection data processor (116) with an anti-correlation filter (118) that filters at least two sets of noisy basis material line integrals, each set corresponding to a different basis material, thereby producing de-noised basis material line integrals, wherein the anti-correlation filter includes a regularization term with regularization balancing factors.

Abstract: Image processing methods and related apparatuses (SEG,UV). The apparatuses (SEG,UV) operate to utilize noise signal information in images (IM). According to one aspect, apparatus (SEG) uses the noise information (FX) to control a model based segmentation. According to a further aspect, apparatus (UV) operates, based on the noise information (FX), to visualize the uncertainty of image information that resides at edge portions of the or an image (IM).

Abstract: A method includes reconstructing measured projection data using an iterative statistical reconstruction algorithm that reduces image artifact caused by differences in variances in projections of the measured projection data used to update a voxel of the image for one or more voxels of the image. A reconstructor includes a processor that reconstructs measured projection data using an iterative statistical reconstruction algorithm that reduces or mitigates image artifact caused by differences in variances in projections used to update a voxel of the image for one or more voxels of the image. A computer readable storage medium encoded with computer executable instructions, which, when executed by a processor of a computer, cause the processor to: reduce image artifact caused by differences in variances in projections used to update a voxel of an image for one or more voxels of the image using an iterative statistical reconstruction algorithm.

Abstract: The noise of a detection value acquired by an imaging system (30) can depend on the contributions of different components within a region of interest to be imaged, which has been traversed by radiation (4) causing the respective acquired detection value. This dependence is considered while iteratively reconstructing an image of the region of interest, wherein first component attenuation values, which correspond to elements of a first component within the region of interest, and second component attenuation values, which correspond to elements of a first component within the region of interest, are determined, wherein noise values are determined from the first component attenuation values and the second component attenuation values and wherein the noise values are used for updating the image. This consideration of the dependence of the noise of an acquired detection value on the different components improves the quality of the iteratively reconstructed image.

Abstract: There is provided a method of determining a transmission quality when receiving audio signals which are transmitted over a frequency-modulated path in analog form. For that purpose a frequency-modulated audio signal is received and IQ demodulation of the input signal is implemented. The I- and the Q-path of the demodulated baseband signal are subjected to analog/digital conversion. Alternatively the input signal can first be digitized and then subjected to IQ demodulation. A multiplicity of N samples is detected. The amount of the N samples is formed. A reference value is determined from the amount of the N samples. Each of the N samples is standardized to the reference value. A measurement in respect of the fluctuations in the standardized amounts is determined. The measurement in respect of the fluctuations indicates the quality of the transmission path.