Abstract: A method is described for the determination of a calcium score for a patient to be examined with the aid of a CT system. The method is used to define patient-specific CT-acquisition parameters. In addition, material parameters for a model method for the generation of synthetic image data for virtual CT-acquisition parameters are calibrated using phantom image data recorded with reference CT-acquisition parameters. A calcium score assigned to synthetic phantom image data corresponds to a calcium score determined with phantom image data recorded with reference CT-acquisition parameters. Next, CT-projection-measurement data is acquired for a region of interest using the patient-specific CT-acquisition parameters. The acquired CT-projection-measurement data is used to generate synthetic image data using the calibrated model method. Finally, a calcium score is determined using a standard method on the basis of the synthetic image data. Also described is a calcium-score-determining device.

Abstract: The present invention relates to a new chemical synthesis, intermediates and catalysts useful for the preparation of the neprilysin (NEP) inhibitor sacubitril. It further relates to new intermediate compounds and their use for said new chemical synthesis route.

Abstract: The present invention relates to a new chemical synthesis, intermediates and catalysts useful for the preparation of the neprilysin (NEP) inhibitor sacubitril. It further relates to new intermediate compounds and their use for said new chemical synthesis route.

Abstract: A method is for generating CT image data with spectral information from an examination region of a patient. According to an embodiment, the examination region is exposed to polychromatic X-radiation. Data from the examination region, including a first projection measurement data record and at least one second projection measurement data record, is captured via a photon counting detector. At least one second projection measurement data record with reduced resolution is generated based upon the at least one second projection measurement data record. The first and at least one second projection measurement data records are then transmitted to an image generation unit. Finally, the resolution of the first projection measurement data record is transferred onto the at least one second projection measurement data record with reduced resolution and/or an image data record based on the at least one second projection measurement data record with reduced resolution. A system is also disclosed.

Abstract: A multi-spectral CT imaging method, preferably a CT imaging method, is described. Spectrally resolved projection scan data is acquired from a region to be imaged of an examination object. The data is assigned to a plurality of pre-determined different partial spectra. Spectrally resolved image data is reconstructed with a plurality of attenuation values for each image point of the region to be imaged. The attenuation values are each assigned to one of the pre-determined different partial spectra. Furthermore, an extremal attenuation value is determined for each image point on the basis of the plurality of attenuation values. A representative image data set is determined such that the determined extremal attenuation value is assigned to each image point.

Abstract: A method is for training a convolutional neural network of a compensation unit. The method includes: provisioning a machine learning device, the machine learning device being designed for training the convolutional neural network; provisioning a start compensation unit, including an untrained convolutional neural network, on or at the machine learning device; provisioning a training image dataset including a plurality of medical training input images and at least one training output image, wherein a reference object is shown essentially without motion artifacts in the at least one training output image and the reference object concerned is contained in the plurality of medical training input images with different motion artifacts; and training the convolutional neural network of the compensation unit in accordance with a principle of machine learning, using the training image dataset. A compensation unit, a machine learning device, a control device for controlling a medical imaging system are also disclosed.

Abstract: A method is disclosed for x-ray CT scanning with a dual-source system, in which two radiation bundles are each delimited by diaphragms such that these radiation bundles are free of mutual points of intersection at least in the examination object. An embodiment of the invention also relates to a dual source CT system, including a controller configured to control radiation-delimiting diaphragms, which delimit and align the radiation bundles such that these run free of mutual points of intersection at least in the examination object.

Abstract: A method is for recognizing artifacts in computed tomography image data. In an embodiment, the method includes acquisition of projection measurement data from a region under examination of a subject to be examined; reconstruction of image data on the basis of the projection measurement data; checking for the presence of an artifact in the image data using a trained recognition unit; recognition of an artifact type of an artifact that is present using a trained recognition unit; and output of the recognized artifact type.

Abstract: A method is for determining classification data for adaption of an examination protocol based on a basic examination protocol of a medical imaging examination as a function of status parameters of the medical imaging examination. In an embodiment, the method includes supplying a set of training data sets, every training data set in each case including a status parameter data set with values of the status parameters of the medical imaging examination and an item of adaption information associated with the status parameter data set. The adaption information relates to an adaption of the examination protocol based on the basic examination protocol of the medical imaging examination, in particular as a function of the status parameters. Finally, the method includes determining the classification data based on a machine learning algorithm and the set of training data sets.

Abstract: The present invention relates to a new chemical synthesis, intermediates and catalysts useful for the preparation of the neprilysin (NEP) inhibitor sacubitril. It further relates to new intermediate compounds and their use for said new chemical synthesis route.

Abstract: A method is for selecting a protocol for a medical imaging examination. In an embodiment, the method includes providing a plurality of protocols; providing a classification system for medical imaging examinations having a plurality of hierarchically ordered categories; determining a node from the quantity of nodes belonging to the set of nodes by which the medical imaging examination can be identified, and to which one protocol respectively is assigned whose category relative to the categories of the other nodes of this quantity is lowest; and selecting the protocol, assigned to the determined node, for the medical imaging examination.

Abstract: A method is for checking a medical image with regard to a processing of the medical image via an image processing module. The method includes providing at least one input requirement of the image processing module relating to at least one image parameter of the medical image; providing the at least one image parameter of the medical image; and checking whether the at least one image parameter fulfills the at least one input requirement.

Abstract: A method is for processing a first image data set including a first image value tuple associated with a volume element of a region of an object to be imaged. In an embodiment, a second image data set is generated based upon the first image data set, including a second image value tuple associated with the volume element, a base material decomposition being capable of being carried based upon the second image data set and based upon a base material set; a starting area and a target area are selected as a function of the base material set, the first image value tuple being located in the starting area; the second image value tuple is ascertained based upon the first image value tuple, the second image value tuple being associated with the first image value tuple via image value tuple imaging and being located in the target area.

Abstract: An example embodiment relates to a method for automatically stipulating a spectral distribution of the X-ray radiation of a number of X-ray sources of a computed tomography system. This involves firstly stipulating start control parameters of an X-ray source, which determine the dose and spectral distribution of X-ray radiation. On the basis of an expected attenuation of the X-ray radiation by an examination object, an examination-object-specific basic control parameter is then ascertained proceeding from the start control parameters. Afterwards, on the basis of the expected attenuation of the X-ray radiation by the examination object and the basic control parameter, first target control parameters and second target control parameters are ascertained for setting the spectral distribution of the X-ray radiation in a subsequent multi-energy measurement on the examination object. Moreover, a method, a control device suitable, and a computed tomography system comprising such a control device are described.

Abstract: A method is for generating CT image data with spectral information from an examination region of a patient. According to an embodiment, the examination region is exposed to polychromatic X-radiation. Data from the examination region, including a first projection measurement data record and at least one second projection measurement data record, is captured via a photon counting detector. At least one second projection measurement data record with reduced resolution is generated based upon the at least one second projection measurement data record. The first and at least one second projection measurement data records are then transmitted to an image generation unit. Finally, the resolution of the first projection measurement data record is transferred onto the at least one second projection measurement data record with reduced resolution and/or an image data record based on the at least one second projection measurement data record with reduced resolution. A system is also disclosed.

Abstract: A method is for generating X-ray image data of an examination object with reduced calcium blooming. The X-ray image data is based on X-ray projection data acquired with an energy-selective X-ray detector and in respect of at least two energy windows. An embodiment of the method includes determining a calcium content in the X-ray projection data by way of a base material analysis, the calcium content describing the calcium-determined part of the X-ray attenuation caused by the examination object; generating a mixed X-ray projection data record with calcium content suppressed by way of a weighting factor of less than one; and reconstructing the X-ray image data from the mixed projection data record by applying a reconstruction algorithm.

Abstract: A method and system are for outputting an item of medical information, the medical information concerning a suitability of a patient for an examination via a medical imaging device and/or the medical information concerning a patient-specific configuration of a medical imaging device, in particular for an examination of a patient. In an embodiment, the method includes acquisition of a measurement data series which relates to at least one physiological parameter of the patient via a first wearable which is worn by the patient; determination of the item of medical information on the basis of the measurement data series; and output of the item of medical information.

Abstract: A method and a system are disclosed for carrying out an imaging medical examination. In an embodiment, the method includes: creation of a decision tree on the basis of training data sets, each including data on patient properties and an assigned scan protocol; selection of a scan protocol based on the decision tree created and a patient data set including data on the patient properties of the patient to be examined; and creation of an image via an imaging device based on the selected scan protocol.

Abstract: A method is described for the determination of a calcium score for a patient to be examined with the aid of a CT system. The method is used to define patient-specific CT-acquisition parameters. In addition, material parameters for a model method for the generation of synthetic image data for virtual CT-acquisition parameters are calibrated using phantom image data recorded with reference CT-acquisition parameters. A calcium score assigned to synthetic phantom image data corresponds to a calcium score determined with phantom image data recorded with reference CT-acquisition parameters. Next, CT-projection-measurement data is acquired for a region of interest using the patient-specific CT-acquisition parameters. The acquired CT-projection-measurement data is used to generate synthetic image data using the calibrated model method. Finally, a calcium score is determined using a standard method on the basis of the synthetic image data. Also described is a calcium-score-determining device.

Abstract: A method is for processing a first image data set including a first image value tuple associated with a volume element of a region of an object to be imaged. In an embodiment, a second image data set is generated based upon the first image data set, including a second image value tuple associated with the volume element, a base material decomposition being capable of being carried based upon the second image data set and based upon a base material set; a starting area and a target area are selected as a function of the base material set, the first image value tuple being located in the starting area; the second image value tuple is ascertained based upon the first image value tuple, the second image value tuple being associated with the first image value tuple via image value tuple imaging and being located in the target area.