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: A container for storing a plurality of food items having a base portion with a peripheral edge at a base peripheral edge plane. The base portion can include a plurality of cavities with each cavity having an interior wall surface extending up a first axis from a cavity base wall. At least a first portion of the interior wall surface terminates at a cavity rim formed where the first portion of the interior wall surface intersects with the peripheral edge surface, wherein an exterior cavity rim portion can be formed by the plurality of cavities. An interior support member formed within the base portion can extend up from the base portion to a first plane above the peripheral edge plane. A lid support member can extend down from the top surface of the lid portion and contact the top surface of the interior support member.

Abstract: A method for assigning a medical device may be implemented in a scheduler agent apparatus. The method may include receiving, from a patient agent apparatus, a utilization request containing patient parameters for examining a patient by a medical device from the group; determining the suitability of at least one medical device from the group for the examination based on the patient parameter or parameters and one or more device parameters; assigning a medical device determined to be suitable to the utilization request based on the patient parameter or parameters and device parameters; transmitting, to the patient agent apparatus, a notification regarding the assignment; and transmitting a notification to an device agent apparatus associated with the assigned medical device.

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: The invention relates to a method for separating waste polyurethane foams, wherein for each polyurethane sample (1) of a supply stream (2) comprising polyurethane samples (1) from waste at least one respective spectrum (3) is recorded, wherein the at least one respective spectrum (3) is recorded by near-infrared spectroscopy, wherein each polyurethane sample (1) of the supply stream (2) is classified by a classification algorithm (5), which classification algorithm (5) is based on machine learning, based on the respective at least one spectrum (3) into a respective class (8a-e) of at least two classes (8a-e), wherein the supply stream (2) comprising polyurethane samples (1) is separated into at least two streams (11a-e) according to the classification into the respective class (8a-e) and wherein each class (8a-e) corresponds to a type of polyurethane. The invention also relates to a system for separating waste polyurethane foams.

Abstract: Systems and methods are provided for optimizing a deep learning model. A multi-site dataset associated with different clinical sites and a deployment dataset associated with a deployment clinical site are received. A deep learning model is trained based on the multi-site dataset. The trained deep learning model is optimized based on the deployment dataset. The optimized trained deep learning model is output.

Abstract: Systems and methods for performing an assessment of a lesion are provided. A plurality of input medical images of a lesion is received. The plurality of input medical images comprises an initial input medical image and one or more additional input medical images. The initial input medical image comprises a region of interest around the lesion. A mask of the lesion is curated for the initial input medical image based on the region of interest and a set of candidate masks. The region of interest in the initial input medical image is propagated to the one or more additional input medical images based on prior registration transformations. A mask of the lesion is curated for each of the one or more additional input medical images based on the propagated regions of interest and the set of candidate masks. One or more assessments of the lesion are performed based on the mask for the initial input medical image, the masks for the one or more additional input medical images, and prior assessments of lesions.

Abstract: In a computer-implemented method of training a machine learning based processor, the processor can be trained to derive image data from signal data sets of multiple spin echo sequences. The trained processor can be configured to perform image processing for Magnetic Resonance Imaging (MRI) to derive the image data.

Abstract: Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

Abstract: Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

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: 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: A brake system for a motor vehicle with at least four hydraulically activated wheel brakes. Each of the wheel brakes has a first electrically activated wheel valve which is open when de-energized and a second electrically activated wheel valve which is closed when de-energized, a first electrically activated pressure source, connected to the first wheel valves via a first brake supply line. Arranged in the first brake supply line is an electrically activated circuit isolating valve by which two of the first wheel valves can be hydraulically disconnected from the first pressure source, a second electrically activated pressure source, and a pressure medium reservoir vessel at atmospheric pressure. The circuit isolating valve is designed to be open when de-energized, and the second electrically activated pressure source is connected to the second wheel valves via a second brake supply line. A method for operating the brake system is also disclosed.

Abstract: Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

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: In a method for generating a biomarker quantifying spatial homogeneity of a medical parameter map, A) the parameter map is provided, B) at least two parameter classes are provided, where each parameter value is to be assigned to a parameter class, C) a sub-area of the examination area is selected, D) in each case, a frequency value for each parameter class for the sub-area is determined, E) a heterogeneity indicator for the sub-area is determined based on the frequency values of the parameter classes, F) further heterogeneity indicators are generated for at least two further sub-areas that are at least partially different from one another, G) a statistical homogeneity value is determined by statistical evaluation of the heterogeneity indicator of the sub-area and the further heterogeneity indicators, and H) the statistical homogeneity value is provided as a biomarker.

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: Systems and methods are provided for classifying an abnormality in a medical image. An input medical image depicting a lesion is received. The lesion is localized in the input medical image using a trained localization network to generate a localization map. The lesion is classified based on the input medical image and the localization map using a trained classification network. The classification of the lesion is output. The trained localization network and the trained classification network are jointly trained.

Abstract: A brake system for a motor vehicle with at least four hydraulically activated wheel brakes. Each of the wheel brakes has a first electrically activated wheel valve which is open when de-energized and a second electrically activated wheel valve which is closed when de-energized, a first electrically activated pressure source, connected to the first wheel valves via a first brake supply line. Arranged in the first brake supply line is an electrically activated circuit isolating valve by which two of the first wheel valves can be hydraulically disconnected from the first pressure source, a second electrically activated pressure source, and a pressure medium reservoir vessel at atmospheric pressure. The circuit isolating valve is designed to be open when de-energized, and the second electrically activated pressure source is connected to the second wheel valves via a second brake supply line. A method for operating the brake system is also disclosed.

Abstract: In a computer-implemented method of training a machine learning based processor, the processor can be trained to derive image data from signal data sets of multiple spin echo sequences. The trained processor can be configured to perform image processing for Magnetic Resonance Imaging (MRI) to derive the image data.