Abstract: A computer-implemented method for predetermining a location and/or a thickness of a slice, to be imaged of a patient during a tomosynthesis imaging to be parameterized by an imaging facility comprising the steps of obtaining three-dimensional image data of a preceding tomosynthesis imaging or of another three-dimensional imaging of the patient, wherein the three-dimensional image data depicts at least one part of an object located at least partly within the patient, evaluating the three-dimensional image data for establishing the location of a longitudinal axis of the object along which the part of the object extends, and establishing the location and/or the thickness of the slice to be imaged as a function of the established location of the longitudinal axis in such a way that the slice to be imaged images a predetermined target position within the patient and at least one longitudinal section of the object when the longitudinal axis of the object is located in the established location.

Abstract: In order to estimate a radiation load quantity for an imaging system having a radiation source, a base model is obtained for determining the radiation load quantity depending on a set of input variables, which include at least one radiation-source operating parameter. Measurement data measured for the imaging system is obtained that includes the radiation load quantity for a multiplicity of different values of the at least one radiation-source operating parameter. A refined model is generated by adapting the base model depending on the measurement data. Actual values of the set of input variables are defined for the imaging system. The refined model is used to determine, depending on the actual values of the set of input variables, an estimated value of the radiation load quantity.

Abstract: A computer-implemented method for providing identification data for a second entity includes: capturing examination data from an imaging-based examination of an examination object by a first entity; providing an abstract vector by applying a trained function to input data, which is based on the examination data of the first entity, wherein the trained function is based on an abstract vector model; and providing the identification data for the second entity on the basis of a similarity comparison of the abstract vector with other abstract vectors in a common abstract vector space stored in a collection, wherein respective identification data is assigned to the stored other abstract vectors. The present disclosure further relates to a computer-implemented method for providing a collection of abstract vectors, a computer-implemented method for providing a trained function, a provision unit, a system, and a computer program product.

Abstract: A monitoring system for monitoring at least one target object in a medical environment.

Abstract: A computer-implemented method for scattered radiation correction, comprising the steps: obtaining projection images, optimizing a measure of quality by variation of correction parameters depending on the projection images, wherein a determination algorithm, which serves to determine the measure of quality, is an algorithm trained by machine learning and processes as its input data a reconstructed three-dimensional image dataset or processing data that is chosen from the image dataset, wherein the image dataset is based on corrected projection images, wherein a respective corrected projection image results from application of a correction algorithm, wherein the correction algorithm is parameterized by the correction parameters, provision of radiation scatter-corrected projection images and/or of a radiation scatter-corrected reconstructed three-dimensional image dataset.

Abstract: A method for operating an X-ray device includes ascertaining a patient model of a patient that describes a surface of the patient, based on patient information. A model position is determined for the patient model in a coordinate system of the X-ray device, in which radiation distribution during an X-ray image acquisition of the examination procedure is also known. The patient model is positioned in accordance with the model position. An X-ray image of the examination procedure, which is acquired for a current patient position of the patient in the X-ray device and exists in the coordinate system of the X-ray device, is supplied as input data to a trained position determination function. Output data from the trained position determination function describes a mapping of a distinguished point of the patient model to a distinguished point of the X-ray image. The model position is determined from the output data.

Abstract: One or more example embodiments relates to a computer-implemented method for determining individual scattered-radiation images for X-ray image points to be considered in an X-ray image.

Abstract: For monitoring a room with a medical technology apparatus, a light projection that defines an areal region in the room is generated with light of a predetermined wavelength characteristic. Using a large number of optical detectors that are each mounted in the areal region and are configured for detecting light having the wavelength characteristic, at least one detector signal is generated. Dependent upon the at least one detector signal, a coverage of at least a portion of the large number of optical detectors by an object is recognized. Dependent upon the recognized coverage, a safety and/or warning measure is initiated.

Abstract: In order to reduce a computing effort for correcting initial images from an imaging apparatus, a scatter model is used to simulate scattered-radiation images, and corresponding initial images are selected from the original initial images. These are used to train a neural network. The neural network may be used to calculate scattered-radiation single images that may be used to correct each individual initial image into a corrected initial image.

Abstract: Systems and methods for providing an overlay data set. The method includes providing a 3D data set that images a vessel, unfolding at least a partial region of the 3D data set along a center line of the vessel to produce a two-dimensional unfolded image, acquiring a first projection of the vessel, registering the first projection with the 3D data set, and providing the overlay data set comprising an overlay of the first projection on the two-dimensional unfolded image.

Abstract: A computer-implemented method for ascertaining an item of environment information is provided. The item of environment information relates to material in surroundings of a third article and/or an interaction of the third article with the material. The method includes receiving an X-ray image and an item of sensor information, and determining model parameters or limiting possible parameter values of the model parameters of a three-dimensional model of the third article as a function of the X-ray image in order to specify an X-ray-dependent model. The three-dimensional model describes a three-dimensional shape and/or pose of the third article as a function of the model parameters. The method includes ascertaining the item of environment information as a function of the X-ray-dependent model, where the item of environment information and/or the X-ray-dependent model additionally depends on the item of sensor information. The item of environment information is provided.

Abstract: A computer-implemented method for determining an estimation of a two-dimensional scattered radiation distribution in a two-dimensional X-ray image that is based on an imaging procedure performed by an X-ray detector is provided. The method includes receiving the X-ray image, applying an estimation algorithm to the X-ray image or to a two-dimensional intermediate image determined from the X-ray image. The estimation algorithm determines a respective two-dimensional partial scattered radiation image for a plurality of physical scatter processes such that image values of pixels of the respective partial scattered radiation image in each case describe an estimated value for a respective scattered radiation dose that was applied to a respective detector region of the X-ray detector assigned to the respective pixel during acquisition of the X-ray image by the respective physical scatter process.

Abstract: A method for operating an X-ray facility for recording a three-dimensional (3D) image data set of a target area of a patient is provided. A recording arrangement including an X-ray detector and an X-ray source may be rotated about an axis of rotation for recording two-dimensional projection images based on the image data set. A model instance of a parameterizable patient model that is patient-specific and 3D is determined. Target area information describing the target area is determined in the model instance from default information. At least two at least partially different partial recording areas of the target area are determined from the target area information. The partial recording areas cover the target area along the axis of rotation. One projection image set is recorded for each of the partial recording areas, and the image data set is reconstructed from the projection image sets.

Abstract: For visual support in a medical intervention on a hollow organ of a patient, reference data that includes a reference representation of the hollow organ is obtained, an X-ray projection image of the hollow organ is generated, and items of overlay information are determined based on the reference data. The reference data includes items of planning information relating to a location of a characteristic feature of the hollow organ in the reference representation. A reference volume is determined in the reference representation as a function of the items of planning information. A reconstruction of a volume of the patient corresponding to the reference volume is generated using a tomosynthesis method. Registration data is generated in that the reference volume is registered in relation to the reconstruction and the items of overlay information are overlaid on the X-ray projection image as a function of the registration data.

Abstract: For denoising medical imaging data, a first imaging dataset and a second imaging dataset are decomposed according to spatial frequency bands to generate high-frequency datasets corresponding to a high-frequency band and low-frequency datasets corresponding to a low-frequency band. A trainable denoising algorithm is trained by carrying out an optimization that uses at least one parameter of the denoising algorithm as an optimization variable and an objective function that depends on a denoised high-frequency dataset and the high-frequency dataset of the second imaging dataset. The denoised high-frequency dataset is generated by applying the denoising algorithm to the high-frequency dataset of the first imaging dataset. The trained denoising algorithm is applied to the high-frequency dataset of the first imaging dataset to generate a final denoised high-frequency dataset.

Abstract: A method for training an algorithm for machine learning for a correction of recordings obtained by an imaging apparatus. A number of output images are recorded. Moreover a smaller number of first, high-quality scattered radiation images are simulated from the output images. A corresponding number of second, low-quality scattered radiation images is further simulated, wherein the simulation is undertaken with a number of photons reduced by at least an order of magnitude. The algorithm is trained with the second, low-quality scattered radiation images as input data and the first, high-quality scattered radiation images as output data.

Abstract: Vessels of a biological object are to be reliably segmented. To this end, a method for training a machine learning algorithm for the purpose of segmenting such vessels is proposed. In the method, a 3D reconstruction is provided with the vessels. A starting vascular region is identified in the 3D reconstruction. Subregions that represent a starting vascular segment are extracted from the starting vascular region. The algorithm is trained with the extracted subregions. The trained algorithm is then applied to a first neighboring region, which is adjacent to the starting vascular region. As a result, a first vascular segment is determined in the first neighboring region. Finally, the algorithm is retrained with the first vascular segment determined in the first neighboring region.

Abstract: A method for providing a classified data set includes capturing an image data set of an examination object by a medical imaging device. The image data set has a plurality of image points in each case with a time-intensity curve. The image points map an examination area of the examination object with at least one contrast-enhanced vascular section. The method further includes identifying first image points in the image data set whose time-intensity curves have a predefined variability as image points that map the at least one contrast-enhanced vascular section, and providing the classified data set based on the image data set and the first image points, wherein the classified data set has a classification between the first image points and further image points of the image data set.

Abstract: A computer-implemented method for specifying the measurement field for an exposure control of an X-ray facility includes: receiving an X-ray image by a computer unit for exposure control; recognizing at least one device marker in the X-ray image; establishing an image shape of the at least one device marker; establishing an image position of the at least one device marker; specifying the position and the shape and/or size of the measurement field dependent upon the image position and the image shape of the at least one device marker; and providing measurement field parameter values that indicate the position, the shape, and/or the size of the measurement field.

Abstract: For particularly rapid and effective scattered-radiation correction of 2D X-ray images, a method is provided for scattered-radiation correction for an X-ray image or a series of X-ray images, which images may be acquired by an acquisition system having an X-ray source, an X-ray detector, and a collimator that shapes the primary X-ray radiation. The method includes: providing the X-ray image acquired in a first setting of the collimator in which setting the object under examination is illuminated; providing an auxiliary X-ray image acquired in a second setting of the collimator in which second setting are illuminated, in particular solely one or more sub-regions of the X-ray detector; subtracting the auxiliary X-ray image from the X-ray image; determining a scattered-radiation correction using image data from the X-ray detector obtained from the subtraction at least in the region of the sub-regions; and correcting the X-ray image using the determined scattered-radiation correction.