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: Computer-implemented method for determining nuclear medical image data sets in dynamic nuclear medical imaging. The method includes using a trained function to determine at least one further nuclear medical image data set for at least one frame if a basis raw data set is taken from one single frame, wherein input data of the trained function includes at least one of the nuclear medical raw data set of the respective frame or a preliminary reconstructed image reconstructed therefrom, and an already determined nuclear medical image data set.

Abstract: Computer-implemented method for determining nuclear medical image data sets in dynamic nuclear medical imaging. The method includes using a trained function to determine at least one further nuclear medical image data set for at least one frame if a basis raw data set is taken from one single frame, wherein input data of the trained function includes at least one of the nuclear medical raw data set of the respective frame or a preliminary reconstructed image reconstructed therefrom, and an already determined nuclear medical image data set.

Abstract: For imaging an object subject to a cyclic motion, two or more imaging repetitions are carried out. Each of the imaging repetitions includes a sequence of equally spaced imaging events, wherein each imaging event has an event number, which corresponds to a respective predefined imaging parameter. A cycle duration of the cyclic motion is determined, a number of events per cycle is determined based on the cycle duration and a shift number is determined at least in part randomly. For a first imaging repetition, a starting number is determined depending on the number of events per cycle and the shift number. The first imaging repetition is carried out, wherein the respective sequence is started with an imaging event, whose event number is given by the starting number.

Abstract: In a method for recording a PET image data set, an overall recording area is moved continuously through the FOV at a constant movement speed, an attenuation map of the overall recording area being used to reconstruct the PET image data record from the PET raw data. The magnetic resonance data of a slice of the patient currently located within the FOV and movement status information relating to a cyclical movement of the patient are recorded simultaneously with recording the PET raw data. A movement status class is assigned to the PET raw data and the magnetic resonance data in each case. Using the magnetic resonance data assigned to the different movement status classes, attenuation maps of the patient are determined for the different movement status classes and applied to the PET raw data assigned to the corresponding movement status class to reconstruct the PET image data set.

Abstract: Systems and methods for reconstructing medical images are disclosed. Measurement data, such as magnetic resonance (MR) data and positron emission tomography (PET) data, is received from an image scanning system. Attenuation maps are generated based on the PET data and a determined background level of radiation of the image scanning system. The background level of radiation can be caused by the radioactive decay of crystal material of the image scanning system. MR images are reconstructed based on the MR data. Further, a neural network, such as a deep learning neural network, is trained with the attenuation maps and the reconstructed MR images to determine attenuation map based on a reconstructed MR image. The trained neural network can be applied to MR data received for a patient to determine a corresponding attenuation map. A final image is generated based on PET data received for the patient and the determined attenuation map.

Abstract: In a method for recording a PET image data set, an overall recording area is moved continuously through the FOV at a constant movement speed, an attenuation map of the overall recording area being used to reconstruct the PET image data record from the PET raw data. The magnetic resonance data of a slice of the patient currently located within the FOV and movement status information relating to a cyclical movement of the patient are recorded simultaneously with recording the PET raw data. A movement status class is assigned to the PET raw data and the magnetic resonance data in each case. Using the magnetic resonance data assigned to the different movement status classes, attenuation maps of the patient are determined for the different movement status classes and applied to the PET raw data assigned to the corresponding movement status class to reconstruct the PET image data set.