Abstract: A method for recording a magnetic resonance image dataset includes providing a magnetic resonance sequence with a series of sequence blocks, and providing at least one correction term to compensate for a magnetic field change. The magnetic field change is produced as a change of an actual magnetic field compared to a setpoint magnetic field by gradient pulses. The magnetic field change is established via a transfer characteristic of the gradient system of the magnetic resonance installation. The at least one correction term is used to compensate for the magnetic field change, and at least one magnetic resonance image dataset is recorded with the magnetic resonance sequence using the correction term.

Abstract: A method for recording a magnetic resonance image dataset includes providing a magnetic resonance sequence with a series of sequence blocks, and providing at least one correction term to compensate for a magnetic field change. The magnetic field change is produced as a change of an actual magnetic field compared to a setpoint magnetic field by gradient pulses. The magnetic field change is established via a transfer characteristic of the gradient system of the magnetic resonance installation. The at least one correction term is used to compensate for the magnetic field change, and at least one magnetic resonance image dataset is recorded with the magnetic resonance sequence using the correction term.

Abstract: A gradient system characterization function (e.g., a gradient system transfer function) may be developed by measuring a behavior of the MR device at a target temperature and developing at least one gradient system characterization function for a gradient coil of a magnetic resonance (MR) device at the target temperature based on the measured behavior. A patient may be subsequently imaged by the MR device, wherein the imaging process comprises measuring a temperature of a gradient coil, determining a gradient system characterization function at the measured temperature, calculating a pre-emphasized gradient of the gradient coil, and imaging the patient using the pre-emphasized magnetic field component.

Abstract: The disclosure relates to methods, devices, and systems for developing gradient system characterization functions and imaging a patient using pre-emphasized magnetic field components in a magnetic resonance (MR) device, wherein the processes allow for a reduction in a number of artifacts when reconstructing the magnetic resonance image. The gradient system characterization function (e.g., a gradient system transfer function) may be developed by measuring a behavior of the MR device at a target temperature and developing at least one gradient system characterization function for a gradient coil of the MR device at the target temperature based on the measured behavior.

Abstract: In a magnetic resonance (MR) method and apparatus, an image reconstruction algorithm is used to reconstruct image data from k-space data that represent an acquired MR signal, and the reconstruction algorithm makes use of a model that requires the MR signal to exhibit a signal behavior from a relaxation model. In order to permit the reconstruction algorithm to be used when the acquired MR signal does not exhibit the model signal behavior due to motion of the subject, the k-space data are motion-corrected so as to produce corrected k-space data that represent said model signal behavior, and image data are reconstructed from the corrected k-space data using the reconstruction algorithm.

Abstract: In a magnetic resonance (MR) method and apparatus, an image reconstruction algorithm is used to reconstruct image data from k-space data that represent an acquired MR signal, and the reconstruction algorithm makes use of a model that requires the MR signal to exhibit a signal behavior from a relaxation model. In order to permit the reconstruction algorithm to be used when the acquired MR signal does not exhibit the model signal behavior due to motion of the subject, the k-space data are motion-corrected so as to produce corrected k-space data that represent said model signal behavior, and image data are reconstructed from the corrected k-space data using the reconstruction algorithm.