Abstract: In a method for an actuation of a magnetic resonance device for capturing image data from an examination region of an examination object, at least one first control sequence is provisioned, the magnetic resonance device is actuated according to the at least one first control sequence to capture first data from the examination object, the first data is analyzed with respect to a property to generate a result, and, based on the result, a selective performance of one of: a selection of a further control sequence, and termination of the actuation of the magnetic resonance device, is performed.

Abstract: In a method for generating a surrogate marker based on medical image data mapping an image region, the medical image data is detected using a first interface, a first subregion of the image region is selected by segmenting a first structure included in the image region, a first property of the first subregion is extracted, the surrogate marker is determined based on the first property, and the surrogate marker is provided using a second interface.

Abstract: A motor vehicle brake system having at least four hydraulically actuatable wheel brakes, including an electrically actuatable inlet valve for each wheel brake. A master brake cylinder actuable by a brake pedal is separably hydraulically connected via an isolation valve to a brake supply line to which the inlet valves are connected, and an electrically controllable pressure-providing device having a pressure space hydraulically connected to the brake supply line. An electrically actuatable circuit isolation valve inline with the brake supply line. With the circuit isolation valve closed the brake supply line is hydraulically separated into first and second line sections. The first line section connected to two of the inlet valves, and the second line section connected to the remaining inlet valves. The pressure space is hydraulically connected to the second line section.

Abstract: A method for determining a contrast agent concentration can be performed after contrast agent administration based on acquired MR images taken before and after contrast agent administration. The method can include the automated steps of determining a model equation describing the contrast agent concentration as a function of a plurality of model parameters, determining values for the plurality of model parameters taking the acquired MR images into account, determining the contrast agent concentration based on the model equation and the values determined, checking whether the contrast agent concentration determined is within an expected value range. If not, determining a corrected contrast agent concentration on the basis of the model equation and a corrected value for at least one of the model parameters. The corrected value for this at least one model parameter is determined such that the contrast agent concentration having the corrected value is within the expected value range.

Abstract: A brake system for a motor vehicle with at least four hydraulically activated wheel brakes, including for each of the wheel brakes an electrically activated first wheel valve which is designed to be open when de-energized and an electrically activated second wheel valve which is designed to be closed when de-energized, a first electrically activated pressure source, which is connected to the first wheel valves via a first brake supply line, a second electrically activated pressure source, and a pressure medium reservoir vessel which is, in particular, at atmospheric pressure, wherein the second electrically activated pressure source is connected to the second wheel valves via a second brake supply line, and a method for operating said brake system.

Abstract: Tissue is characterized using machine-learnt classification. The prognosis, diagnosis or evidence in the form of a similar case is found by machine-learnt classification from features extracted from frames of medical scan data. The texture features for tissue characterization may be learned using deep learning. Using the features, therapy response is predicted from magnetic resonance functional measures before and after treatment in one example. Using the machine-learnt classification, the number of measures after treatment may be reduced as compared to RECIST for predicting the outcome of the treatment, allowing earlier termination or alteration of the therapy.

Abstract: A method is disclosed for determining result data based upon medical measurement data of an examination object. Within the method, a high-dimensional first parameter space is formed, in which measurement values of the various measurements are represented with the aid of value tuples. The measurement values of the various measurements are assigned to a value tuple based on their spatial arrangement in the examination object and/or on their temporal arrangement relative to one another. In the first parameter space, the value tuples are analyzed, using at least one mapping function to at least one further parameter space including a lower dimension than the first parameter space, in order to obtain result data. Furthermore, the result data is output, preferably visualized. In addition, a corresponding device for determining result data is described.

Abstract: A magnetic resonance method and system are provided for magnetic resonance (MR) image-guided insertion of an object into a biological tissue along a predetermined trajectory. The trajectory provides a path between a starting point and a target site within the tissue. Sufficiently high resolution images can be generated in real time to precisely guide the needle placement. A compressed sensing approach is used to generate the images based on minimization of a cost function, where the cost function is based on the predetermined needle path, artifact effects associated with the needle, the negligible changes in the images away from the trajectory, and the limited differences between successive images. The improved combination of spatial and temporal resolution facilitates an insertion procedure that can be continuously adjusted to accurately follow a predetermined trajectory in the tissue, without interruptions to obtain verification images.

Abstract: In a method and apparatus for generating a two-dimensional projection image from a three-dimensional image data set of an examination object, a three-dimensional image data set of the examination object having a number of voxels is provided to a computer wherein one scan value is associated with one voxel of the examination object. The computer determines at least one value from voxels respectively located along a viewing direction of the three-dimensional image data set, and their scan values, using at least one selection criterion. The at least one determined value is a value that differs from an upper limit value and a lower limit value of the scan values of the voxels located along the viewing direction. The at least one value is used for generating an image point in the two-dimensional projection image.

Abstract: For the creation of a magnetic resonance (MR) image of a predetermined volume section of an object of investigation, MR data of the volume section are collected along radial trajectories, and each trajectory is assigned a readout direction in which the MR data are collected along the respective trajectory. The MR image is reconstructed on the basis of the collected MR data. In the reconstruction, only MR data are taken into consideration that were collected along trajectories with a readout direction restricted to the field of a solid angle that is defined by a partial surface of a sphere. The partial surface (A) at most corresponds to 75% of the total surface of the sphere.

Abstract: A method and apparatus for automated prostate tumor detection and classification in multi-parametric magnetic resonance imaging (MRI) is disclosed. A multi-parametric MRI image set of a patient, including a plurality of different types of MRI images, is received. Simultaneous detection and classification of prostate tumors in the multi-parametric MRI image set of the patient are performed using a trained multi-channel image-to-image convolutional encoder-decoder that inputs multiple MRI images of the multi-parametric MRI image set of the patient and includes a plurality of output channels corresponding to a plurality of different tumor classes. For each output channel, the trained image-to image convolutional encoder-decoder generates a respective response map that provides detected locations of prostate tumors of the corresponding tumor class in the multi-parametric MRI image set of the patient.

Abstract: A brake system for a motor vehicle having hydraulically actuatable wheel brakes. Each wheel an electrically actuatable inlet valve and electrically actuatable outlet valve for setting wheel-specific brake pressures. A first electrically controllable pressure provision device is connected to a brake supply line to which the wheel brakes are connected. A second electrically controllable pressure provision device is connected to the brake supply line. A first electrical device activates the first pressure provision device. A second electrical device activates the second pressure provision device. Electrically independent first and second electrical partitions are provided. The first pressure provision device and the first electrical device are assigned to the first electrical partition and the second pressure provision device, the second electrical device and the inlet and outlet valves are assigned to the second electrical partition. The inlet and outlet valves are activated by the second electrical device.

Abstract: For radial sampling in magnetic resonance imaging (MRI), a rescaling factor is determined from k-space data for each coil. The rescale factor is inversely proportional to the streak energy in the k-space data. The k-space data from the coils is rescaled for reconstruction, such as weighting the k-space data by the rescale factor in a data consistency term of iterative reconstruction. The rescale factor is additionally or alternatively used to determine a correction field for correction of intensity bias applied to intensities in the image-object space after reconstruction. These approaches may result in a diagnostically useful bias-corrected image with reduced streak artifact while benefiting from the efficient computation (i.e., computer operates to reconstruct more quickly).

Abstract: In a method and system for generating a magnetic resonance image, a raw data record with non-Cartesian recorded data points is provided to a processor, and the recorded data points are gridded on a Cartesian grid to form transformed data points, wherein the number of transformed data points is selected in at least one k-space direction such that the field of view is reduced in size, and Fourier transformation of the transformed data points is implemented to form a magnetic resonance image with a field of view as the raw data record that is smaller in at least one direction.

Abstract: A method is disclosed for creating a motion correction for PET data acquired by a PET system from a volume segment of an examination object. The method includes acquisition of MR data within the volume segment by the magnetic resonance system; and determination of a motion model of a motion within the volume segment as a function of the MR data. The motion model, as a function of a respective motion state of the motion, provides a correction specification for PET data which is acquired during this motion state. During acquisition of the MR data, specific MR data is acquired in the center of the k-space or of a straight-line segment which passes through the center of the k-space. The MR data determined is converted by a mathematical function into one value, as a function of which the respective motion state is determined.

Abstract: A method and apparatus for automated prostate tumor detection and classification in multi-parametric magnetic resonance imaging (MRI) is disclosed. A multi-parametric MRI image set of a patient, including a plurality of different types of MRI images, is received. Simultaneous detection and classification of prostate tumors in the multi-parametric MRI image set of the patient are performed using a trained multi-channel image-to-image convolutional encoder-decoder that inputs multiple MRI images of the multi-parametric MRI image set of the patient and includes a plurality of output channels corresponding to a plurality of different tumor classes. For each output channel, the trained image-to image convolutional encoder-decoder generates a respective response map that provides detected locations of prostate tumors of the corresponding tumor class in the multi-parametric MRI image set of the patient.

Abstract: In a method and apparatus for generating a two-dimensional projection image from a three-dimensional image data set of an examination object, a three-dimensional image data set of the examination object having a number of voxels is provided to a computer wherein one scan value is associated with one voxel of the examination object. The computer determines at least one value from voxels respectively located along a viewing direction of the three-dimensional image data set, and their scan values, using at least one selection criterion. The at least one determined value is a value that differs from an upper limit value and a lower limit value of the scan values of the voxels located along the viewing direction. The at least one value is used for generating an image point in the two-dimensional projection image.

Abstract: Method to acquire a magnetic resonance data set of an acquisition area (5) in a subject (O) via radial scanning along a fixed number of spokes (6) respectively described by a first angle in k-space, wherein the acquisition area (5) deviates in positional space from a circular shape in a shape that can be described by the set of first angles; wherein the acquisition of the spokes (6) takes place according to an acquisition order; wherein an acquisition position of the acquisition order is associated with each first angle under consideration of a comparison data set of the fixed number of second angles (in which second angles of successive acquisition positions differ by a golden angle) such that, for a first angle of each acquisition position, the spatially adjacent first angles have the same acquisition positions as the second angles spatially adjacent to a second angle of the acquisition position.

Abstract: Tissue is characterized using machine-learnt classification. The prognosis, diagnosis or evidence in the form of a similar case is found by machine-learnt classification from features extracted from frames of medical scan data. The texture features for tissue characterization may be learned using deep learning. Using the features, therapy response is predicted from magnetic resonance functional measures before and after treatment in one example. Using the machine-learnt classification, the number of measures after treatment may be reduced as compared to RECIST for predicting the outcome of the treatment, allowing earlier termination or alteration of the therapy.

Abstract: A method is disclosed for determining result data based upon medical measurement data of an examination object. Within the method, a high-dimensional first parameter space is formed, in which measurement values of the various measurements are represented with the aid of value tuples. The measurement values of the various measurements are assigned to a value tuple based on their spatial arrangement in the examination object and/or on their temporal arrangement relative to one another. In the first parameter space, the value tuples are analyzed, using at least one mapping function to at least one further parameter space including a lower dimension than the first parameter space, in order to obtain result data. Furthermore, the result data is output, preferably visualized. In addition, a corresponding device for determining result ata is described.