Abstract: An image processing system (IPS) and related method to transform different multi-modal or multi-contrast input images (u,v) into respective transformed images (U,V). The transformation may proceed iteratively to improve a regularized objective function. The regularization is via a regularizer function (R). The regularizer function (R) is computed from noise normalized gradients of the two or more transformed images (u,v).

Abstract: The present invention relates to an image reconstruction system for statistically reconstructing images from transmission measurements. The image reconstruction system comprises an update equation providing unit for providing an update equation based on an iterative statistical model. The update equation comprises a data term and a regularization term. The invention proposes to not modify the regularization term, but rather the weights with which individual measurements contribute are modified on a per image voxel and per measurement basis. This is achieved by modifying the contributions of each measurement by including an additional weight on a per image voxel/per measurement basis. The additional weight for each measurement is determined by calculating the noise perpendicular to each measurement ray at each voxel position and a voxel and measurement dependent weight for each measurement, and integrated into the update equation's data term.

Abstract: The present invention relates to a device (100) for denoising a vector-valued image, the device (100) comprising: a generator (10), which is configured to generate an initial loss function (L_I) comprising at least one initial covariance matrix (ICM) defining a model of correlated noise for each pixel of the vector-valued image; a processor (20), which is configured to provide a final loss function (L_F) comprising a set of at least one final covariance matrix (FCM) based on the initial loss function by modifying at least one submatrix and/or at least one matrix element of the initial covariance matrix (ICM); and a noise-suppressor (30), which is configured to denoise the vector-valued image using the fmal loss function (L_F) comprising the set of the at least one fmal covariance matrix (FCM).

Abstract: An image processing apparatus (IP) comprising an input port (IN) for receiving projection data through respective 3D locations in an imaging region, said projection date collected in a scan operation by an imaging apparatus (IM). An image segment generator (IGS) of said apparatus (IP) is configured to generate, based on said projection data, a first image segment for said 3D locations. A visualizer (VIZ) configured to effect displaying said first image segment on a display device before or whilst the image apparatus collects projection data for a different 3D location.

Abstract: The present invention relates to a device for reconstructing an X-ray tomography image, the device comprising a reconstruction module, which is configured to utilize an ordered subset maximum likelihood optimization with a diagonal paraboloid approximation of a cost function for the reconstructing of the X-ray tomography image; and a calculation module, which is configured to calculate a pre-computable denominator term for the cost function for a plurality of subsets of projection data based on a distribution of diagonal denominator terms over the plurality of the subsets of the projection data.

Abstract: The invention relates to peripheral equalization during a mammography X-ray examination. High contrast tissue pixel values are removed from the background estimate by finding the minimum intensity values of the pixel located in the neighborhood, which have approximately the same distance to the skin line. Thus, high attenuating pixel values may be removed from the estimate and replaced by lower attenuating tissue pixel values. After a minimum filtration, a conventional peripheral equalization is performed. This may result in less overshoots and intensity values for higher attenuating structures in the peripheral region may become more consistent with intensity values for higher attenuating structures in the fully compressed region.

Abstract: A system includes obtaining de-noised reconstructed image data and edge improving a sub-set of the de-noised reconstructed image data corresponding to edges of structure represented in the de-noise reconstructed image data. A system (100) includes an edge detector (202) that detects an edge map of edge locations within de-noised reconstructed image data, a noise image data generator (204) that generates noise image data by subtracting the reconstructed image data by the de-noised reconstructed image data, a noisy edge image data generator (206) that generates noisy edge image data by multiplying the noise image data and the edge map, and an edge improver (208) that generates edge improved de-noised image data by adding the noisy edge image data and a product of a weight and the de-noised reconstructed image data.

Abstract: An image processing system (IPS) and related method to transform different multi-modal or multi-contrast input images (u,v) into respective transformed images (U, V). The transformation may proceed iteratively to improve a regularized objective function. The regularization is via a regularizer function (R). The regularizer function (R) is computed from noise normalized gradients of the two or more transformed images (u,v).

Abstract: The invention relates to peripheral equalization during a mammography X-ray examination. High contrast tissue pixel values are removed from the background estimate by finding the minimum intensity values of the pixel located in the neighbourhood, which have approximately the same distance to the skin line. Thus, high attenuating pixel values may be removed from the estimate and replaced by lower attenuating tissue pixel values. After a minimum filtration, a conventional peripheral equalization is performed. This may result in less overshoots and intensity values for higher attenuating structures in the peripheral region may become more consistent with intensity values for higher attenuating structures in the fully compressed region.

Abstract: The present invention relates to a device (100) for iterative reconstruction of images recorded by at least two imaging methods, the device comprising: an extraction module (10), which is configured to extract a first set of patches from a first image recorded by a first imaging method and to extract a second set of patches from a second image recorded by a second imaging method; a generation module (20), which is configured to generate a set of reference patches based on a merging of a first limited number of atoms for the first set of patches and of a second limited number of atoms for the second set of patches; and a regularization module (30), which is configured to perform a regularization of the first image or the second image by means of the generated set of reference patches.

Abstract: The present invention relates to a detection device (6) for detecting photons emitted by a radiation source (2). The detection device (6) is configured to detect the photons during a first time period. The detection device (6) comprises a sensor (10) having an intermediate direct conversion material for converting photons into electrons and holes, a shaping element (20), and a compensation unit (450, INT, 950). The compensation unit (450, INT, 950) is adapted to provide a compensation signal based on the electrical pulse and on a photoconductive gain of said sensor (10). The core of the invention is to provide circuits to reduce artifacts due to inherent errors with direct conversion detectors in spectral computed tomography by determining a compensation current, by detecting or monitoring a baseline restorer feedback signal, or by ignoring signals above the baseline level.

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: The present invention relates to a device for tomosynthesis imaging, the device comprising: a mask generator module (101) configured to generate a binary mask based on a geometric three-dimensional model of a scanned object; an image capturing module (102) configured to scan a series of two-dimensional projection images of the object; and an image processing module (103) configured to apply the generated binary mask during a reconstruction of a three-dimensional image volume from the scanned series of two-dimensional projection images and to restrict an extent of the reconstructed image volume to the extent of the geometric model.

Abstract: The present invention relates to a device (100) for iterative reconstruction of images recorded by at least two imaging methods, the device comprising: an extraction module (10), which is configured to extract a first set of patches from a first image recorded by a first imaging method and to extract a second set of patches from a second image recorded by a second imaging method; a generation module (20), which is configured to generate a set of reference patches based on a merging of a first limited number of atoms for the first set of patches and of a second limited number of atoms for the second set of patches; and a regularization module (30), which is configured to perform a regularization of the first image or the second image by means of the generated set of reference patches.

Abstract: The present invention relates to a device for tomosynthesis imaging, the device comprising: a mask generator module (101) configured to generate a binary mask based on a geometric three-dimensional model of a scanned object; an image capturing module (102) configured to scan a series of two-dimensional projection images of the object; and an image processing module (103) configured to apply the generated binary mask during a reconstruction of a three-dimensional image volume from the scanned series of two-dimensional projection images and to restrict an extent of the reconstructed image volume to the extent of the geometric model.

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: The present invention relates to a detection device (6) for detecting photons emitted by a radiation source (2). The detection device (6) is configured to detect the photons during a first time period. The detection device (6) comprises a sensor (10) having an intermediate direct conversion material for converting photons into electrons and holes, a shaping element (20), and a compensation unit (450, INT, 950). The compensation unit (450, INT, 950) is adapted to provide a compensation signal based on the electrical pulse and on a photoconductive gain of said sensor (10). The core of the invention is to provide circuits to reduce artifacts due to inherent errors with direct conversion detectors in spectral computed tomography by determining a compensation current, by detecting or monitoring a baseline restorer feedback signal, or by ignoring signals above the baseline level.

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 system includes obtaining de-noised reconstructed image data and edge improving a sub-set of the de-noised reconstructed image data corresponding to edges of structure represented in the de-noise reconstructed image data. A system (100) includes an edge detector (202) that detects an edge map of edge locations within de-noised reconstructed image data, a noise image data generator (204) that generates noise image data by subtracting the reconstructed image data by the de-noised reconstructed image data, a noisy edge image data generator (206) that generates noisy edge image data by multiplying the noise image data image data and a product of a weight and the de-noised reconstructed image data.

Abstract: A processing component (122) processes images based on an iterative reconstruction algorithm with regularization and/or de-noising algorithm. The processing component includes a set point determiner (224) that determines a quality set point (216) between predetermined lower and upper quality bounds (226) based on a quality variable (228) indicative of an image quality of interest. The processing component further includes a comparator (214) that compares, each processing iteration, a quality metric of a current generated image with the quality set point and generates a difference value indicative of a difference between the quality metric and the quality set point.