Abstract: A computer-implemented method for providing a 3D image dataset includes identifying an acquisition plan and an acquisition trajectory. The method further includes determining a collimator configuration of a collimation unit for each acquisition positioning, wherein each collimator configuration specifies a spatial arrangement of at least one filter element of the collimation unit such that: X-ray radiation that is emitted by the X-ray source and illuminates a detector row without earlier passing through the volume of interest is filtered, and X-ray radiation that is emitted by the X-ray source and illuminates at least part of a detector row after passing through the volume of interest is transmitted. The method further includes acquiring the X-ray projection images of the object under examination, wherein the collimation unit is adjusted based on the collimator configurations; providing the 3D image dataset by reconstruction from the X-ray projection images.

Abstract: The disclosure provides solutions for reducing exposure to radiation in digital subtraction angiography. For this, a method for generating a virtual mask image is proposed. A plurality of images of an object is captured by an angiography apparatus. For at least some of all pixel positions, an extreme pixel value of the pixels of the plurality of images in the respective pixel position is respectively ascertained. The virtual mask image is created from the extreme pixel values at the respective pixel positions.

Abstract: The invention relates to a method for identifying a change in truncation of an examination object between first projection photographs of the examination object generated by a CT apparatus, and second projection photographs of the examination object generated by the CT apparatus, comprising the following steps to be carried out by a control facility. Receiving a first dataset, comprising the first projection photographs of the examination object; receiving a second dataset, comprising the second projection photographs of the examination object; correlating the first dataset with the second dataset; establishing the change in truncation of the examination object between the first projection photographs and the second projection photographs when satisfaction of at least one predefined change criterion between the datasets is captured; and outputting a predetermined output signal when the change in truncation between the first projection photographs and the second projection photographs is established.

Abstract: A computer-implemented method for providing a vascular image data record includes receiving a plurality of projection-X-ray images recorded in temporal succession. The plurality of projection-X-ray images at least partially map a common examination region of an examination object. The plurality of projection-X-ray images map a temporal change in the examination region of the examination object. A change image data record is determined in each case based on at least one region of interest of the plurality of projection-X-ray images. The at least one region of interest includes a plurality of image points. The change image data record in each case includes a time-intensity curve for each of the image points. The vascular image data record is generated based on the change image data record, and the vascular image data record is provided.

Abstract: First projection images are recorded. The first projection images map an examination object along different first projection directions. A corresponding respective second projection image is recorded for at least two first projection images. The first projection images each have a first focus point, and the second projection images each have a second focus point. Each of the second projection images together with a corresponding first projection image at least partially map a common part of the examination object about a stationary center point. The second projection images map the examination object along second projection directions that are mutually different and at least partially different, relative to the respectively corresponding first projection directions such that a straight line through the first focus point and the second focus point of the mutually corresponding first projection images and second projection images extends through the stationary center point.

Abstract: A computer-implemented method comprises: providing at least two exploratory views; segmenting a first object in the at least two exploratory views to determine first two-dimensional object masks; segmenting the second object in the at least two exploratory views tow determine second two-dimensional object masks; determining a first three-dimensional object mask as a function of the first two-dimensional object masks; determining a second three-dimensional object mask as a function of the second two-dimensional object masks; and determining an overlap of the first object and the second object for at least one capture trajectory as a function of the first three-dimensional object mask and the second three-dimensional object mask.

Abstract: A computer-implemented method for providing a result dataset, comprising: acquisition of at least one projection mapping pair of an object under examination by a medical biplane imaging device, wherein the at least one projection mapping pair contains a first and a second projection mapping of the object under examination, that map the object under examination simultaneously in a first and a second detection plane, wherein the first and second detection plane are arranged non-parallel to one another, determination of a correction model for the correction of an artifact and/or a movement, wherein the artifact and/or the movement is mapped simultaneously in the at least one first and the at least one second projection mapping, wherein the at least one projection mapping pair specifies a consistency condition for the determination of the correction model, reconstruction of the result dataset at least from the at least one first projection mapping and on the basis of the correction model, provision of the result

Abstract: Systems and methods for quantification of an influence of scattered radiation in the analysis of an object a projection image is provided. Based on the projection image and on a characteristic of a tomography facility and/or of the object relating to the influence of the scattered radiation, at least one intermediate image is created. The at least one intermediate image is analyzed using an artificial neural network to quantify the influence of the scattered radiation.

Abstract: A method for generating a subtraction image for digital subtraction angiography to reduce noise and movement artifacts. Obtaining a plurality of mask images of an object takes place before administering a contrast agent into the object and obtaining a map of the object after administering a contrast agent into the object. A first sum image is obtained from the plurality of mask images in that the plurality of mask images is summed in each case multiplied by an individual weighting. The individual weightings for each of the plurality of mask images are automatically determined by an optimization method, and the subtraction image is ascertained by subtraction of the sum image from the map.

Abstract: A computer-implemented method is for providing a difference image data record. In an embodiment, the method includes a determination of a first real image data record of an examination volume in respect of a first X-ray energy, and a determination of a multi-energetic real image data record of the examination volume in respect of a first X-ray energy and a second X-ray energy, the second X-ray energy differing from the first X-ray energy. The method further includes the determination of the difference image data record of the examination volume by applying a trained function to input data, wherein the input data is based upon the first real image data record and the multi-energetic real image data record, as well as the provision of the difference image data record.

Abstract: A computer-implemented method for reconstruction of medical image data includes receiving medical measuring data, and minimizing a cost value via gradient descent. Minimizing the cost value includes: reconstructing the medical image data by applying a reconstruction function to the received medical measuring data in accordance with reconstruction parameters; determining a cost value by applying a cost function to the reconstructed medical image data; determining a gradient of the cost function with respect to the reconstruction parameters; adjusting the reconstruction parameters based on the gradient of the cost function with respect to the reconstruction parameters and the previous reconstruction parameters; and providing the adjusted reconstruction parameters. The acts of the minimizing are repeated until a termination condition is met. The reconstructed medical image data is provided.

Abstract: A method for providing an optimum subtraction data set includes: receiving first image data sets acquired by a medical imaging device and which map an object under examination within a first time phase; receiving at least one second image data set acquired by the same or another medical imaging device and which maps a change in the object under examination within a second time phase; dividing the at least one second image data set into a plurality of image regions; generating subtraction image regions for the plurality of image regions; determining an image quality parameter for each subtraction image region; determining an optimum subtraction image region for each image region of the plurality of image regions of the at least one second image data set by comparing the image quality parameters; generating the optimum subtraction data set from the optimum subtraction image regions; and providing the optimum subtraction data set.

Abstract: A computer-implemented method includes, in an embodiment, receiving first X-ray projections of an examination volume in respect of a first X-ray energy and second X-ray projections in respect of a second X-ray energy, the first and second X-ray energies differing. The method further includes determination of a multienergetic real image data record of the examination volume based upon the first and second X-ray projections; selection of first voxels of the multienergetic real image data record based upon the multienergetic real image data record; selection of second voxels of the multienergetic real image data record based upon the first X-ray projections and the second X-ray projections, the first voxels including the second voxels and the second voxels mapping contrast medium in the examination volume. The method further includes provision of a constraint image data record and/or a difference image data record based upon the second voxels.

Abstract: A method includes receiving image data of an examination object. A first temporary data record is created by applying a first correction to the image data. A further temporary data record is created by applying a further correction to the image data. The further correction at least partially corresponds to the first correction. A trained function is applied to input data that is based on the first temporary data record and the further temporary data record. A parameter of the trained function is based on an image quality metric. It is determined whether the first temporary data record has a higher image quality compared with the further temporary data record. When a result is positive, the first temporary data record is provided as the corrected medical image data. When the result is negative, the further temporary data record is provided as the image data, and part of the method is repeated.

Abstract: A method for providing an optimum subtraction data set includes receiving first image data sets that are recorded by a medical imaging device and map an examination object within a first temporal phase. At least one second image data set that maps the examination object within a second temporal phase and is recorded by the same or another medical imaging device is received. Mask data sets are determined. The mask data sets include at least one of the first image data sets and/or an averaging of at least one combination of the first image data sets. Subtraction data sets are generated by subtracting one of the mask data sets from the at least one second image data set, and an image quality parameter is determined for each of the subtraction data sets. An optimum subtraction data set is provided by a comparison of the image quality parameters.

Abstract: A method for providing an optimum subtraction data set includes: receiving first image data sets acquired by a medical imaging device and which map an object under examination within a first time phase; receiving at least one second image data set acquired by the same or another medical imaging device and which maps a change in the object under examination within a second time phase; dividing the at least one second image data set into a plurality of image regions; generating subtraction image regions for the plurality of image regions; determining an image quality parameter for each subtraction image region; determining an optimum subtraction image region for each image region of the plurality of image regions of the at least one second image data set by comparing the image quality parameters; generating the optimum subtraction data set from the optimum subtraction image regions; and providing the optimum subtraction data set.

Abstract: A method for segmenting metal objects in projection images acquired using different projection geometries is provided. Each projection image shows a region of interest. A three-dimensional x-ray image is reconstructed from the projection images in the region of interest. A trained artificial intelligence segmentation algorithm is used to calculate first binary metal masks for each projection image. A three-dimensional intermediate data set of a reconstruction region that is larger than the region of interest is reconstructed by determining, for each voxel of the intermediate data set, as a metal value, a number of first binary metal masks showing metal in a pixel associated with a ray crossing the voxel. A three-dimensional binary metal mask is determined. Second binary metal masks are determined for each projection image by forward projecting the three-dimensional binary metal mask using the respective projection geometries.

Abstract: Systems and methods are provided for reconstructing a three-dimensional result image data set from computed tomography from a plurality of two-dimensional images that create an image of an object undergoing examination from a particular imaging angle, The imaging angles of all the images lie within a restricted angular range. A three-dimensional artifact-reduced image data set is provided based on the two-dimensional images using an algorithm for reducing artifacts that are the result of a restriction of the angular range. The result image data set is reconstructed using a reconstruction algorithm that processes both the artifact-reduced image data set and the two-dimensional images as input data.

Abstract: First projection images are recorded. The first projection images map an examination object along different first projection directions. A corresponding respective second projection image is recorded for at least two first projection images. The first projection images each have a first focus point, and the second projection images each have a second focus point. Each of the second projection images together with a corresponding first projection image at least partially map a common part of the examination object about a stationary center point. The second projection images map the examination object along second projection directions that are mutually different and at least partially different, relative to the respectively corresponding first projection directions such that a straight line through the first focus point and the second focus point of the mutually corresponding first projection images and second projection images extends through the stationary center point.

Abstract: A method and system for automatically adapting an image data set obtained by an X-ray device. Binary masks are generated for single images of the image data set. The masks differentiate different components of an imaged target object from each other. A reference image of the image data set is determined therefrom, that contains a largest cohesive region of one of the components. From a mean value determined for the region and a specified target value, an offset is determined in such a way that by applying it to the pixel values used for determining the mean value. The pixel values are adapted in such a way that a mean value of the pixel values adapted by the offset corresponds to the specified target value. The determined offset is then applied to all pixel values of the image data set in order to adapt the image data set.