Abstract: Systems and methods for determining a target imaging protocol for an image acquisition are provided. At least one of 1) one or more performance indicators, 2) an input imaging protocol for an image acquisition, or 3) changes in conditions of the image acquisition are received. A target imaging protocol is determined using an image acquisition model based on the at least one of the one or more performance indicators, the input imaging protocol, or the changes in the conditions of the image acquisition. The target imaging protocol are output.

Abstract: For automatically determining a configuration for magnetic resonance imaging (MRI), an initial scanner model for an MRI scanner is received. The initial scanner model specifies a deviation of a main magnetic field from a predefined target main magnetic field and/or a deviation of a magnetic field gradient from a predefined target gradient field. MRI measurement data measured by using the MRI scanner is received. A first updated scanner model is generated by applying a trained first machine learning model (MLM) to first input data that depends on the initial scanner model and the MRI measurement data. The configuration for MRI is determined depending on the first updated scanner model.

Abstract: Techniques are described for providing image-based operational decision support. The technique includes using a decision engine configured to generate output data based on a determined number of clinical findings in medical images of a patient. The decision module is configured to generate decision data depending on position data defining an actual position of the patient in a predefined clinical guideline, which comprises a set of possible next steps subsequent to the actual position. The decision data comprises information indicating which next steps from the set of possible next steps of the clinical guideline should be performed. The disclosure further describes a related method, a clinical decision system, and a related medical imaging system.

Abstract: Techniques are described for providing image-based operational decision support. The technique includes providing initial imaging data from a preceding examination of a patient, determining clinical findings by automated processing of the initial imaging data, generating decision data at least comprising a decision whether a further recording of a number of images is necessary, and generating a suggested set of imaging parameter values for recording this number of images. The decision data may be based on the determined clinical findings, and the technique may further include outputting the suggested set of imaging parameter values for recording a number of images of the patient. Also described are a related clinical decision system, a decision module, and a related medical imaging system.

Abstract: A magnetic resonance (MR) system compensation interface having: a hardware subinterface configured to receive individual hardware parameters from an individual scan unit of an MR system; a model determination unit configured to determine an imperfection model on the basis of the hardware parameters; a compensation model determination unit configured to determine a compensation model on the basis of the imperfection model; an application subinterface configured to receive application data assigned to an application; and a compensation unit configured to determine compensated application data on the basis of the received application data and the determined compensation model.

Abstract: Techniques are described for detecting a specified substance in an examination object by way of a magnetic resonance apparatus. A controller ascertains a magnetic resonance sequence comprising at least one sub-sequence for detecting at least one substance to be detected in the examination object as a function of the at least one substance to be detected, and ascertains at least one measuring instant for capturing a respective MRT signal to detect the at least one substance to be detected in the examination object as a function of the at least one substance to be detected. The at least one MRT signal is evaluated for fulfillment of a predetermined detection condition, and a presence of the at least one substance to be detected is established when the at least one MRT signal fulfils the predetermined detection condition.

Abstract: A magnetic resonance (MR) system compensation interface having: a hardware subinterface configured to receive individual hardware parameters from an individual scan unit of an MR system; a model determination unit configured to determine an imperfection model on the basis of the hardware parameters; a compensation model determination unit configured to determine a compensation model on the basis of the imperfection model; an application subinterface configured to receive application data assigned to an application; and a compensation unit configured to determine compensated application data on the basis of the received application data and the determined compensation model.

Abstract: Techniques are described for providing image-based operational decision support. The technique includes using a decision engine configured to generate output data based on a determined number of clinical findings in medical images of a patient. The decision module is configured to generate decision data depending on position data defining an actual position of the patient in a predefined clinical guideline, which comprises a set of possible next steps subsequent to the actual position. The decision data comprises information indicating which next steps from the set of possible next steps of the clinical guideline should be performed. The disclosure further describes a related method, a clinical decision system, and a related medical imaging system.

Abstract: Techniques are described for providing image-based operational decision support. The technique includes providing initial imaging data from a preceding examination of a patient, determining clinical findings by automated processing of the initial imaging data, generating decision data at least comprising a decision whether a further recording of a number of images is necessary, and generating a suggested set of imaging parameter values for recording this number of images. The decision data may be based on the determined clinical findings, and the technique may further include outputting the suggested set of imaging parameter values for recording a number of images of the patient. Also described are a related clinical decision system, a decision module, and a related medical imaging system.

Abstract: In a method for executing at least one application on a magnetic resonance (MR) device, the at least one application is stored on a separately implemented memory, a communication and/or data exchange is performed with the at least one application using an interface of the MR device, at least one item of hardware information relating to the MR device is communicated to the at least one application using an information channel of the interface, at least one parameter of the at least one application is matched to the at least one item of hardware information of the MR device, and at least one item of control information is provided using a control channel of the interface, by the at least one application of the magnetic resonance device, to execute the at least one application.

Abstract: A magnetic resonance apparatus has a scanner that has a patient receiving area, a position data acquisition unit, and a patient examination table of a patient positioning device. The table is movable within the patient receiving area. The position data acquisition unit detects a subarea, including an isocenter, of the patient receiving area, and provides position data to a speed regulating processor that regulates the speed of the table of patient positioning device depending on this position data.

Abstract: In a method for providing a selection of at least one protocol parameter from a plurality of protocol parameters for a user-defined protocol parameter setting of at least one magnetic resonance protocol for a magnetic resonance examination on a patient using a magnetic resonance device, a selection mode and a setting mode can be performed. In the selection mode, stored user-dependent parameter information can be provided and a selection of the at least one protocol parameter for a protocol parameter setting can be determined based on the stored user-dependent parameter information. In the setting mode, the determined selection of the at least one protocol parameter can be provided to the user via a user interface.

Abstract: A medical imaging apparatus has a data acquisition scanner having a patient receiving zone at least partially enclosed by the scanner, and at least one acquisition unit equipped with a camera to acquire positional data. The at least one acquisition unit has a first imaging optics system and at least one second imaging optics system that differs from the first imaging optics system with regard to at least one optical property or attribute that affects the acquisition of the positional data.

Abstract: A flexible magnetic resonance coil apparatus, an applicator, and a method for arranging a magnetic resonance coil apparatus on an object under examination are provided. The magnetic resonance coil apparatus includes at least one coil element and at least one carrier structure. The at least one carrier structure is configured to adapt its geometric shape.

Abstract: A machine-learnt classifier is used for more anonymous data transfer. Deep learning, such as neural network machine learning, results in a classifier with multiple distinct layers. Each layer processes the output of a preceding layer. As compared to the input to the layer, the output is different. By applying a subset of layers locally, the resulting output may be provided to a cloud server for application to the remaining layers. Since the output of a layer of the deep-learnt classifier is different than the input, the information transmitted to and available at the cloud server is more anonymous or different than the original data, yet the cloud server may apply the latest machine learnt classifier as the remaining layers.

Abstract: In a method for providing a selection of at least one protocol parameter from a plurality of protocol parameters for a user-defined protocol parameter setting of at least one magnetic resonance protocol for a magnetic resonance examination on a patient using a magnetic resonance device, a selection mode and a setting mode can be performed. In the selection mode, stored user-dependent parameter information can be provided and a selection of the at least one protocol parameter for a protocol parameter setting can be determined based on the stored user-dependent parameter information. In the setting mode, the determined selection of the at least one protocol parameter can be provided to the user via a user interface.

Abstract: A medical imaging apparatus has a data acquisition scanner having a patient receiving zone at least partially enclosed by the scanner, and at least one acquisition unit equipped with a camera to acquire positional data. The at least one acquisition unit has a first imaging optics system and at least one second imaging optics system that differs from the first imaging optics system with regard to at least one optical property or attribute that affects the acquisition of the positional data.

Abstract: A magnetic resonance coil apparatus, a magnetic resonance apparatus and a method for handling a magnetic resonance coil apparatus are provided. The magnetic resonance coil apparatus includes a first coil unit and a second coil unit. The first coil unit and the second coil unit are configured to rotate about a longitudinal axis relative to one another.

Abstract: A flexible magnetic resonance coil apparatus, an applicator, and a method for arranging a magnetic resonance coil apparatus on an object under examination are provided. The magnetic resonance coil apparatus includes at least one coil element and at least one carrier structure. The at least one carrier structure is configured to adapt its geometric shape.