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: In an embodiment, a first real image dataset of an examination volume is received. The examination volume includes a vessel here, and the first real image dataset maps the examination volume includes contrast medium. Furthermore a differential image dataset of the examination volume is determined by application of a first trained generator function to input data. Here the input data includes the first real image dataset and a parameter of the trained generator function based on a GA algorithm. Furthermore the differential image dataset is provided.

Abstract: For a particularly comprehensive identification of hollow organ systems, a method is provided for producing a digital subtraction angiography of a hollow organ system of a patient. The method includes: providing mask image data recorded by an X-ray device; providing at least first fill image data recorded by the X-ray device, which has been recorded during an at least partial filling of the hollow organ system with a contrast agent; starting from a first intravenous and a second intraarterial contrast agent injection following in time; ascertaining at least first subtraction image data by subtracting the mask image data from the at least first fill image data; ascertaining final subtraction image data from the at least first subtraction image data; and segmenting the final subtraction image data and assigning the pixels or voxels of the final subtraction image data to at least two different intensity classes based on their respective intensity value.

Abstract: Described herein are technologies for facilitating reconstruction of flow data. In accordance with one aspect, the framework receives a four-dimensional projection image dataset and registers one or more pairs of temporally adjacent projection images in the image dataset. Two-dimensional flow maps may be determined based on the registered pairs. The framework may then sort the two-dimensional flow maps according to heart phases, and reconstruct a three-dimensional flow map based on the sorted two-dimensional flow maps.

Abstract: A method for actuating an X-ray device during robot-assisted navigation of at least two objects introduced into a body, such as a hollow organ, of a patient by at least one robotic system, includes providing a first selection criterion for selecting one of the objects, and providing a second selection criterion for selecting one of the objects. One of the at least two objects is selected based on the first selection criterion and the second selection criterion, and recording parameters of the X-ray device are automatically set, such that the selected object in an X-ray image to be recorded is highlighted compared to the at least one other object. The selected object may be highlighted with respect to image quality, image flavor, positioning on the X-ray image, and/or a collimator setting of a collimator of the X-ray device. An X-ray image is recorded with the set recording parameters.

Abstract: A method is provided for adapting an image impression of an image, in particular of an image acquired in the context of medical imaging.

Abstract: A method is provided for producing a high-resolution three-dimensional digital subtraction angiography image of an examination object. The method includes: providing or recording of a data set of a three-dimensional rotational run of an imaging system around the examination object without administration of contrast agent (e.g., mask run); motion compensation of the data set of the mask run by a method based on the epipolar consistency conditions; providing or recording of a data set of a three-dimensional rotational run of the imaging system around the examination object with administration of contrast agent (e.g., fill run); motion compensation of the data set of the fill run by a method based on the epipolar consistency conditions; reconstructing a first volume from the compensated data set of the mask run (e.g., mask volume) and a second volume from the compensated data set of the fill run (e.g.

Abstract: An inverse visualization of a time-resolved angiographic image data set of a vascular system of a patient that was recorded by a medical imager during the flow of a contrast medium through the vascular system is provided. The time-resolved angiographic image data set of the vascular system has a temporal sequence of frames of the vascular system corresponding to the contrast medium filling process. A data set from bolus arrival times for each pixel or voxel is determined. The bolus arrival time corresponds to the time in the temporal sequence at which a predetermined contrast enhancement due to the contrast medium filling first occurs. A data set of temporally inverted bolus arrival times with respect to the contrast medium filling is determined for each pixel or voxel, resulting in a temporally inverted sequence of frames with respect to the contrast medium filling. The time-resolved angiographic image data set in the temporally inverted sequence is visualized.

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: A solution for determination of a three-dimensional difference image dataset of an examination volume. Here two-dimensional real image datasets relating to the examination volume are received via an interface, each of the two-dimensional real image datasets including a two-dimensional x-ray projection of the examination volume in relation to a projection direction. Furthermore, the first difference image dataset is determined based on the two-dimensional real image datasets and based on a first trained function via a processing unit. Here the first difference image dataset is at least two-dimensional, in particular at least three-dimensional, in particular the first difference image dataset is three-dimensional or four-dimensional. The determination of the first difference image dataset based on the two-dimensional real image datasets and based on a trained function enables mask recordings of the examination volume to be dispensed with, and thus the x-ray load of the examination volume to be reduced.

Abstract: A framework for quantitative evaluation of time-varying data. In accordance with one aspect, the framework delineates a volume of interest in a four-dimensional (4D) Digital Subtraction Angiography (DSA) dataset (204). The framework then extracts a centerline of the volume of interest (206). In response to receiving one or more user-selected points along the centerline (208), the framework determines at least one blood dynamics measure associated with the one or more user-selected points (210), and generates a visualization based on the blood dynamics measure (212).

Abstract: For a particularly comprehensive identification of hollow organ systems, a method is provided for producing a digital subtraction angiography of a hollow organ system of a patient. The method includes: providing mask image data recorded by an X-ray device; providing at least first fill image data recorded by the X-ray device, which has been recorded during an at least partial filling of the hollow organ system with a contrast agent; starting from a first intravenous and a second intraarterial contrast agent injection following in time; ascertaining at least first subtraction image data by subtracting the mask image data from the at least first fill image data; ascertaining final subtraction image data from the at least first subtraction image data; and segmenting the final subtraction image data and assigning the pixels or voxels of the final subtraction image data to at least two different intensity classes based on their respective intensity value.

Abstract: A method and computing unit are for automatically checking a superposition image of a body region of interest of an examination object. The method and computing unit include determining at least one reference position of an object in a reference image; determining a current position of the object; generating the superposition image by superimposing the current fluoroscopic image and the reference image; determining at least one parameter characterizing a measure of discrepancy; and displaying the measure of discrepancy determined. Further, in at least one embodiment, the various aspects of the method or performed by at least one processor of the computing unit, are performed in quasi real time.

Abstract: A system and method for providing an evaluation dataset from a first medical three-dimensional computed tomography dataset. The method includes reconstructing the first three-dimensional computed tomography dataset from a plurality of two-dimensional X-ray projection images recorded with different acquisition geometries from an examination object by a medical X-ray device and providing an artifact-reduced image dataset. Providing includes applying a method for reducing artifacts to the first computed tomography dataset. The method further includes identifying for example hemorrhagic and/or ischemic stroke indications by applying an method for identifying stroke indications to the artifact-reduced image dataset, creating an evaluation dataset by applying an method for evaluating a manifestation of the identified stroke indications to the artifact-reduced image dataset, and providing the evaluation dataset.

Abstract: In an embodiment, a first real image dataset of an examination volume is received. The examination volume includes a vessel here, and the first real image dataset maps the examination volume includes contrast medium. Furthermore a differential image dataset of the examination volume is determined by application of a first trained generator function to input data. Here the input data includes the first real image dataset and a parameter of the trained generator function based on a GA algorithm. Furthermore the differential image dataset is provided.

Abstract: Some embodiments relate to solutions to providing a result image data set. At least one embodiment is based on an input image data set of a first examination volume being received. A result image parameter is received or determined. A result image data set of the first examination volume is determined by application of a trained generator function to input data. Input data is based on the input image data set and the result image parameter, and the result image parameter relates to a property of the result image data set. A parameter of the trained generator function is based on a GA algorithm (acronym for the English technical term “generative adversarial”). Finally, the result image data set is provided. Some embodiments relate to solutions for providing a trained generator function and/or a trained classifier function, in particular for use in solutions for providing a result image data set.

Abstract: A method is provided for determining corrected acquisition geometries of projection images. The method includes providing a projection image dataset that has a plurality of projection images of an object under examination acquired by an acquisition device in different acquisition geometries. The method further includes determining a provisional acquisition geometry for each of the projection images by a first optimization method by minimizing a first cost function by varying the provisional acquisition geometry, wherein the first cost function is contingent on a plurality of consistency measures determined based on the provisional acquisition geometry for a respective pair of projection images.

Abstract: Methods and systems are disclosed herein for improved safer planning support during interventional procedures for inserting stents into a hollow organ of a patient by a guide device. One method includes: providing or recording a three-dimensional image data set of the hollow organ in a first position; segmentation or providing a segmentation of the three-dimensional image data set; providing or recording a two-dimensional image of the guide device introduced into the hollow organ; overlaying the three-dimensional image data set with the two-dimensional image; determining at least one corrected position of one or more section(s) of the hollow organ respectively using the overlaying of the three-dimensional image data set with the two-dimensional image; and determining the respective deformation energy of the hollow organ in the section(s) for the case of removal of the guide device using the previously determined corrected position compared to the first position.

Abstract: A method is provided for determining corrected acquisition geometries of projection images. The method includes providing a projection image dataset that has a plurality of projection images of an object under examination acquired by an acquisition device in different acquisition geometries. The method further includes determining a provisional acquisition geometry for each of the projection images by a first optimization method by minimizing a first cost function by varying the provisional acquisition geometry, wherein the first cost function is contingent on a plurality of consistency measures determined based on the provisional acquisition geometry for a respective pair of projection images.

Abstract: A method for digital subtraction angiography of a recording region of a patient is provided herein. The method includes recording at least one mask image of a recording region without using a contrast medium; recording a plurality of ill images after administration of a contrast medium; and determining result images by subtraction of one of the at least one mask image from respective fill images.