Disclosed herein is a magnetic resonance imaging system (100) controlled by a processor (130). The execution of the machine executable instructions causes the processor to sort (200) multiple preparatory scan commands (142) into fixed duration preparatory scan commands (144) and indeterminate duration preparatory scan commands (146). The execution of the machine executable instructions further causes the processor to first control (202) the magnetic resonance imaging system with the indeterminate duration preparatory scan commands and then (204) with the fixed duration preparatory scan commands. The execution of the machine executable instructions further causes the processor to calculate (206) a gradient pulse starting time (160). The execution of the machine executable instructions further causes the processor to provide (208) the warning signal at a predetermined time (162) before the gradient pulse starting time. The execution of the machine executable instructions further causes the processor to control (210) the magnetic resonance imaging system with pulse sequence commands to acquire the k-space data such that the execution of the gradient coil pulse commands begins at the pulse starting time.

A system and method comprises execution of a segmented magnetic resonance imaging pulse sequence, the pulse sequence including a plurality of shots, each of the plurality of shots including an inversion recovery preparation pulse and acquiring a respective segment of k-space lines, wherein each shot comprises a different inversion time between a peak of the inversion recovery pulse and a midpoint of the acquisition of the respective segment of k-space lines, and reconstruction of an image based on the acquired respective segments of k-space lines. In some aspects, the k-space lines acquired by each shot are consecutive in a phase encoding direction of k-space and each shot acquires the segments of k-space lines acquired by prior shots in the sequence, and a time delay between the inversion recovery preparation pulse and acquisition of a first segment for each shot is equal. In other aspects, each shot acquires its respective segment using interleaved reordering and the time delay between the inversion recovery preparation pulse and acquisition of the respective segment for each shot is different.

A magnetic resonance (MR) imaging system includes a transmit radio frequency (RF) coil assembly comprising multiple capacitor banks each coupled to at least one diode that is characterized by a high breakdown voltage such that when the transmit RF coil assembly applies at least one slice-selecting RF pulse to a portion of a subject placed in the magnet to select a particular slice for MR imaging, the capacitor banks are selectively adjusted to improve an RF transmission characteristics of the RF coil assembly in transmitting the at least one slice-selecting RF pulse. The MR imaging system may further include a receive radio frequency (RF) coil assembly configured to, in response to at least the slice-selecting RF pulse, receive at least one response radio frequency (RF) pulse emitted from the selected slice of the portion of the subject; a housing; a main magnet; gradient coils; and a control unit.

In a method for MRI of an object, spins of a first material and spins of a second material are excited. An in-phase echo signal is acquired when the spins are in-phase and an out-of-phase echo signal is acquired, when the spins are out of phase. A first image for the first material and/or a second image for the second material is generated by a computing unit depending on the in-phase echo signal and the out-of-phase echo signal. For acquiring the out-of-phase echo signal, a momentum space is sampled asymmetrically in a read-out direction.

The present disclosure discloses a magnetic resonance imaging method based on a blade sequence. The method can include acquiring 3-D data collected by a surface coil, determining a corresponding plurality of kernel data of each blade from the 3-D data according to the position information of each blade, collecting a corresponding plurality of slices of aliasing K-space data of each blade, performing convolution operations for the corresponding plurality of slices of aliasing K-space data of each blade and the corresponding plurality of kernel data of each blade to obtain a corresponding plurality of unaliasing K-space data of each blade, and reconstructing images for the corresponding plurality of unaliasing K-space data of different blades to obtain a plurality of unaliasing images. The present disclosure further describes a magnetic resonance imaging device for realizing the method and a computer-readable storage medium.

A method for generating a magnetic resonance image includes providing MR segment data records, wherein each MR segment data record has N×M frequency voxels in k-space. To reduce the acquisition time during MR segment recordings, the amount of MR data is reduced by incompletely sampling the k-space during a recording. The missing data of the MR segment data records are reconstructed twice: Preliminarily reconstructed MR segment data records are calculated first, with a reconstruction kernel obtained from reference data. Modified reference images containing phase information are obtained by creating phase images from the preliminarily reconstructed MR segment data records and combining these phase images with the absolute value of the reference image generated from the reference data. The second reconstruction kernels are ascertained therefrom in turn. In contrast to the first reconstruction kernel, these contain phase information, such that the missing data can be reconstructed without phase artifacts.

Abstract: Disclosed herein is a medical system comprising a memory (110) storing machine executable instructions (120) and a trained neural network (122). The trained neural network is configured to output corrected magnetic resonance image data (130) in response to receiving as input a set of magnetic resonance images (126) each having a different spatially constant frequency off-resonance factor. The medical system further comprises a computational system (106) configured for controlling the medical system, wherein execution of the machine executable instructions causes the computational system to: receive (200) k-space data (124) acquired according to a magnetic resonance imaging protocol; reconstruct (202) a set of magnetic resonance images (126) according to the magnetic resonance imaging protocol, wherein each of the set of magnetic resonance images is reconstructed assuming a different spatially constant frequency off-resonance factor chosen from a list of frequency off-resonance factors (128); and receive (204) the corrected magnetic resonance image data in response to inputting the set of magnetic resonance images into the trained neural network.

A plurality of reception coils are used to acquire magnetic resonance signals using parallel imaging and a k-space acquisition scheme, in which alternatingly the central region and one of the peripheral k-space portions are imaged in acquisition steps of a pair, such that after a partition number of such pairs, the whole k-space to be acquired has been imaged and a sliding reconstruction window can be applied to reconstruct an additional magnetic resonance image after each acquisition of such a pair. A time series of magnetic resonance images forming the magnetic resonance data set is then reconstructed from the magnetic resonance signals and sensitivity information regarding the plurality of reception coils by using the sliding reconstruction window and a reconstruction technique for undersampled magnetic resonance data. The k-space trajectories for each acquisition step are chosen to allow controlled aliasing in all three spatial dimensions including the readout direction.

Described here are systems and methods for a robust magnetic resonance elastography (“MRE”) imaging platform for rapid dynamic 3D MRE imaging. The imaging platform includes an MRE pulse sequence and advanced image reconstruction framework that work synergistically in order to greatly expand the domains where MRE can be deployed successfully.

Systems and methods for image reconstruction for parallel MR imaging are disclosed that receive a k-space single-coil measurement dataset that includes at least two k-space single-coil measurement sets, transforming the k-space single-coil measurement dataset to an estimated CSM using a coil sensitivity estimation module, and transforming the k-space single-coil measurement dataset and the estimated CSM into a final MR image using an MRI reconstruction module. In some aspects, the coil sensitivity estimation module and MRI reconstruction module include deep learning neural networks trained without the use of ground truth data.