Abstract: A computer-implemented method of an embodiment is for automatically estimating and/or correcting an error due to artifacts in a multi-energy computed tomography result dataset relating to at least one target material. In an embodiment, the method includes determining at least one first subregion of the imaging region, which is free from the target material and contains at least one, in particular exactly one, second material with known material-specific energy dependence of x-ray attenuation; for each first subregion, comparing the image values of the energy dataset for each voxel, taking into account the known energy dependence, to determine deviation values indicative of artifacts; and for at least a part of the at least one remaining second subregion of the imaging region, calculating estimated deviation values by interpolating and/or extrapolating from the determined deviation values in the first subregion, the estimated deviation values being used as estimated error due to artifacts.

Abstract: Embodiments of the present invention relates to an X-ray contrast agent. The X-ray contrast agent has an X-ray absorption the change of which between at least two different X-ray photon energy levels differs from the change in X-ray absorption of calcium between the at least two different X-ray photon energy level. Embodiments of the present invention also relates to an X-ray imaging method. Embodiments of the present invention additionally relates to an image reconstruction device. Embodiments of the present invention further relates to an X-ray imaging system.

Abstract: A method for providing thermal conductivity data relating to an anatomical structure, comprises: receiving first spectral computed tomography data relating to the anatomical structure; calculating a fat map of the anatomical structure and a water map of the anatomical structure based on the first spectral computed tomography data; calculating the thermal conductivity data relating to the anatomical structure based on the fat map and the water map; and providing the thermal conductivity data.

Abstract: A computer-implemented method comprises: receiving a measurement data set, the measurement data set including energy resolved data based on a computed tomography scan of the patient; reconstructing a morphology preserving image data set based on a first photon-energy band or a first combination of photon-energy bands described by the measurement data set; segmenting a blood pool within a myocardium in the morphology preserving image data set; reconstructing a contrast agent map based on a second photon-energy band or a second combination of photon-energy bands described by the measurement data set; determining a reference value based on at least one pixel or voxel of the contrast agent map within the segmented blood pool; and determining a respective myocardial extracellular volume fraction depending on the reference value and a value given for at least one respective pixel or voxel outside the segmented blood pool by the contrast agent map.

Abstract: A method for determining a quantitative result CT parameter map in a region of interest of an object under examination is described. The method includes acquiring a sequence of quantitative input CT parameter maps for at least two predetermined times, the sequence being generated by a contrast-enhanced spectral multiphase CT of the region of interest; receiving a sequence of contrast-enhanced MRI image datasets, the MRI datasets having a higher temporal resolution than the sequence of input CT parameter maps; determining a relation between the MRI image datasets and the input CT parameter maps; and determining the result CT parameter map based on the determined relation and the MRI image datasets for at least one additional time, the at least one additional time being different from the predetermined time.

Abstract: A first image data set and at least one second image data set are captured, and a contrast-enhanced image data set and a non-contrast image data set are determined based on the first and the at least one second image data set. The perfusion image data set is calculated based on a ratio of image values of the contrast-enhanced image data set and locally corresponding image values of the non-contrast image data set, and the perfusion image data set is provided via a second interface.

Abstract: One or more example embodiments relates to a method for supporting a determination of a vessel morphology on the basis of spectral CT information. Furthermore, one or more example embodiments comprises an apparatus, a control facility and a medical technology system.

Abstract: In a method for spectrally differentiated cardiac CT imaging, first spectrally differentiated CT projection measurement data relating to a heart is received in a first time interval, when a contrast agent is located in chambers and/or vessels of the heart. The first time interval comprises a diastole of the heart. Second spectrally differentiated CT projection measurement data relating to the heart is received in a second time interval, when the contrast agent is located in a muscle tissue of the heart. The second time interval includes a systole of the heart. First monoenergetic image data is calculated for a first energy value based on the first spectrally differentiated CT projection measurement data and second monoenergetic image data is calculated for the first energy value based on the second spectrally differentiated CT projection measurement data.

Abstract: An arc resistant switch gear comprises a switchgear enclosure including a circuit breaker a high voltage door and enclosure door latch and sealing mechanisms. These mechanisms are configured to provide a combination of latching and sealing functionality to seal and latch the switchgear enclosure with the high voltage door via a door latching and sealing system in combination with a latch part and a door frame. To remove the circuit breaker out of the switchgear enclosure a door sealing slider which is in the switchgear enclosure must be removed.

Abstract: At least one vascular tree supplying at least a part of the hollow organ in the computed tomography dataset is segmented, and a tree structure up to an order possible based on the blood vessel segmentation result is determined from a blood vessel segmentation result. Perfusion information for each edge in the tree structure is assigned as at least one of the computed tomography data assigned to the blood vessel segment or at least one value derived therefrom. Adjacent hollow organ segments of the hollow organ are defined based on supply by adjacent blood vessels in the tree structure, and the tree structure and the perfusion information are analyzed to determine hemodynamic information to assign to hollow organ segments. At least a part of the hemodynamic information in at least one of the computed tomography dataset or a visualization dataset derived therefrom is then visualized.

Abstract: A system and method include acquisition of a two-dimensional radiograph of a patient, input of the radiograph to a trained machine learning model to generate a classification, performance of a computed tomography scan of the patient based on the two-dimensional radiograph if the classification indicates that the patient does not have a first condition, and determination to modify the computed tomography scan if the classification indicates that the patient has the first condition.

Abstract: An imaging method is described for generating image data of an examination region of an object that is to be examined. First X-ray projection measurement data of the examination region is acquired using a first X-ray energy spectrum and at least second X-ray projection measurement data of the examination region is acquired using a second X-ray energy spectrum which is different from the first X-ray energy spectrum. A priori image data is reconstructed based on at least the first X-ray projection measurement data and a location-dependent distribution of X-ray attenuation values. A basis material decomposition is performed based on the first X-ray projection measurement data and the at least second X-ray projection measurement data. A location-dependent weighting of the basis materials is determined as a function of the location-dependent distribution of the X-ray attenuation values. An image for the examination region is determined by reconstructing virtual basis-material-weighted image data.

Abstract: One or more example embodiments relates to a method for controlling a computed tomography system, the method comprising defining an examination region of an examination object; defining a number of interfering structures, wherein an interfering structure is a structure located within a beam path of the computed tomography system and reflects or absorbs X-ray radiation with a strength outside of a tolerance range; calculating beam paths of X-rays of a CT examination of the examination region and ascertaining interference angle ranges of a gantry of the computed tomography system at which the beam paths run through the interfering structure and the examination region; carrying out a CT scan while the gantry rotates, and recording CT data; reconstructing an image dataset from CT data of the recorded CT data excluding the ascertained interference angle ranges; and outputting the image dataset.

Abstract: A computer-implemented method of an embodiment is for automatically estimating and/or correcting an error due to artifacts in a multi-energy computed tomography result dataset relating to at least one target material. In an embodiment, the method includes determining at least one first subregion of the imaging region, which is free from the target material and contains at least one, in particular exactly one, second material with known material-specific energy dependence of x-ray attenuation; for each first subregion, comparing the image values of the energy dataset for each voxel, taking into account the known energy dependence, to determine deviation values indicative of artifacts; and for at least a part of the at least one remaining second subregion of the imaging region, calculating estimated deviation values by interpolating and/or extrapolating from the determined deviation values in the first subregion, the estimated deviation values being used as estimated error due to artifacts.

Abstract: An operating method comprises: triggering administration of a first contrast medium application for presaturation of the body region with contrast medium, wherein the first contrast medium application is administered to achieve a desired equilibrium concentration; triggering administration of a second contrast medium application in the form of a bolus larger than in the first contrast medium application; recording spectral image data at at least two different beam energies; reconstructing images from the spectral image data; and outputting the images.

Abstract: The present disclosure relates to a heat press, especially knee lever-transfer press with at least one socket, with at least one base plate and with at least one heatable counter plate pivotable towards the base plate, wherein the knee lever-transfer press further has a control unit, by which the knee lever-transfer press is controllable in an open-loop manner and/or closed-loop manner and wherein the control unit constitutes a first modular unit of the knee lever-transfer press and wherein the socket constitutes at least one second modular unit, and the base plate and the counter plate constitute at least one third modular unit and wherein at least the first modular unit and the second modular unit and/or the third modular unit are separable from each other and/or are formed to be replaceable for functional comparable modular units.

Abstract: One or more example embodiments provides a method for evaluating an angiographic dual-energy computed tomography dataset recorded using a contrast agent comprising iodine to determine a quantitative calcium score.

Abstract: A method is for noise reduction in image recordings. In an embodiment, the method includes providing an input image; de-noising the input image and producing a de-noised input image; and adapting noise texture of pixels of the de-noised input image via an adaptation method, noise amplitude of the de-noised input image being largely retained and the noise texture of the pixels of the de-noised input image being adapted to correspond largely to a defined noise texture. A corresponding device, a production method for an adaptation device, such an adaptation device, and a control facility and a computed tomography system are also disclosed.

Abstract: In one embodiment, a method is for calculating an examination parameter for a computed tomography examination of an area of interest of a patient. The method includes receiving a topogram of the area of interest of the patient; determining fat distribution information by applying a trained machine learning algorithm onto the topogram; and calculating the examination parameter for the computed tomography examination of the area of interest of the patient based on the fat distribution information.

Abstract: An analysis method is for automatically determining radiological result data from radiology data sets. In an embodiment, the method includes provisioning a first radiology data set at least based on X-ray data of a first X-ray energy spectrum; provisioning at least one second radiology data set at least based on X-ray data of a second X-ray energy spectrum; provisioning an analysis unit including a neural network, to analyze radiology data sets including an input layer with a plurality of cells, a number of intermediate layers and an output layer representing a radiological result; analyzing the first radiology data set and the at least one second radiology data set, at least subsets of the first radiology data set and the at least one second radiology data set being assigned to different cells of the input layer for joint processing in the neural network; and acquiring result data on the output layer.