In a method for correction of a B0 field map measured with a magnetic resonance device, that describes deviations from a nominal field strength in the homogeneity area of the magnetic resonance device by deviations from a nominal frequency for protons bonded to water, the deviations being represented as Larmor frequency values for different picture elements shifted by chemical shifts, the B0 field map is recorded with spins of the fat and water protons not in phase. The B0 field map is segmented by evaluating the differences of the Larmor frequency values of adjacent picture elements of the B0 field map in at least two contiguous clusters. For each cluster, a decision is made on the basis of a smoothness criterion and a compactness criterion as to whether a cluster containing a majority of protons bonded into fat is involved. Clusters identified as containing a majority of protons bonded into fat are corrected by lowering the Larmor frequency values by the difference between the nominal frequency for protons bonded into water and the corresponding nominal frequency for protons bonded to fat.

The invention relates to a method of MR imaging of a body (10) of a patient. It is an object of the invention to provide a method that enables efficient compensation of flow artifacts, especially for MR angiography in combination with Dixon water/fat separation. The method of the invention comprises the steps of: a) generating MR echo signals at two or more echo times by subjecting the portion of the body (10) to a MR imaging sequence of RF pulses and switched magnetic field gradients, wherein the MR imaging sequence is a Dixon sequence; b) acquiring the MR echo signals; c) reconstructing one or more single-echo MR images from the MR echo signals; d) segmenting the blood vessels from the MR images; e) detecting and compensating for blood flow-induced variations of the amplitude or phase in the single-echo MR images within the blood vessel lumen, and f) separating signal contributions from water and fat spins to the compensated single-echo MR images. Moreover, the invention relates to a MR device (1) and to a computer program for a MR device (1).

Described herein are systems and methods for the selective mapping of water T1 relaxation times.

For determination of motion artifact in MR imaging, motion of the patient in three dimensions is used with a measurement k-space line order based on one or more actual imaging sequences to generate training data. The MR scan of the ground truth three-dimensional (3D) representation subjected to 3D motion is simulated using the realistic line order. The difference between the resulting reconstructed 3D representation and the ground truth 3D representation is used in machine-based deep learning to train a network to predict motion artifact or level given an input 3D representation from a scan of a patient. The architecture of the network may be defined to deal with anisotropic data from the MR scan.

At least two gradient echo signals are generated at two different echo times by subjecting a portion of a body (10) in an MR examination region (1) to an imaging sequence of RF pulses and switched magnetic field gradients. The 0th moment of the readout magnetic field gradient essentially vanishes at the time of a first gradient echo while the 1st moment of the readout gradient is non-zero. Both the 0th and 1st moments of the readout magnetic field gradient essentially vanish at a time of a second gradient echo. Gradient echo signals are acquired. Acquiring the gradient echo signals is repeated for a plurality of phase encoding steps. A first MR image is reconstructed from the gradient echo signals of the first gradient echo and a second MR image is reconstructed from the gradient echo signals of the second gradient echo. Ghosting artefacts in the first and/or second MR image are identified by comparing the first and second MR images.

The disclosure relates to techniques for perming chemical exchange saturation transfer (CEST) imaging correction. The present disclosure improves the speed of correcting CEST images.

Disclosed herein is a medical system (100, 300, 500) comprising a memory (110) storing machine executable instructions (120) and a convolutional neural network (122). The convolutional neural network is configured for receiving an initial Dixon magnetic resonance image (124, 126) as input. The convolutional neural network is configured for identifying one or more water-fat swap regions (128) in the initial Dixon magnetic resonance image. The medical system further comprises a processor (104) for controlling the medical system. Execution of the machine executable instructions causes the processor to: receive (200) the initial Dixon magnetic resonance image; and receive (204) the one or more water-fat swap regions from the convolutional neural network in response to inputting the initial Dixon magnetic resonance image into the convolutional neural network.

A magnetic resonance imaging apparatus according to an embodiment includes processing circuitry configured, on a basis of one or both of (A) a parameter related to applying one of inversion and flip pulses and (B) an intensity of a slice selecting gradient magnetic field applied together with the one of the pulses in relation to selecting a slice to which the one of the pulses is applied, to determine one or both of (A) a parameter related to applying the other of the inversion and (B) flip pulses; and an intensity of the slice selecting gradient magnetic field applied together with the other of the pulses in relation to selecting a slice to which the other of the pulses is applied.

The disclosure relates to techniques for perming chemical exchange saturation transfer (CEST) imaging correction. The present disclosure improves the speed of correcting CEST images.

Improved magnetic resonance imaging systems, methods and software are described including a low field strength main magnet, a gradient coil assembly, an RF coil system, and a control system configured for the acquisition and processing of magnetic resonance imaging data from a patient while utilizing a sparse sampling imaging technique.