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.

The present disclosure may provide imaging methods, systems and storage media. The imaging methods may include: obtaining first imaging data acquired by an imaging device, wherein the first imaging data includes data corresponding to a plurality of cardiac cycles; and performing image reconstruction on data corresponding to the plurality of cardiac cycles in the first imaging data to acquire one or more cardiac cines. Each cardiac cine of the one or more cardiac cines may include cardiac images of a plurality of phases in at least one cardiac cycle.

In a computer-implemented method of training a machine learning based processor, the processor can be trained to derive image data from signal data sets of multiple spin echo sequences. The trained processor can be configured to perform image processing for Magnetic Resonance Imaging (MRI) to derive the image data.

A computer implemented method for providing output data comprising an indication regarding the affliction of a patient with an infectious respiratory disease, the method comprises receiving magnetic resonance imaging data, the magnetic resonance imaging data acquired using a magnetic resonance imaging system, the magnetic resonance imaging data comprising a lung region of the patient; applying a trained function to the magnetic resonance imaging data to generate the output data, the trained function being based on an artificial neural network and the output data comprising the indication regarding the affliction of the patience with the infectious respiratory disease; and proving the output data.

Systems and methods for generating MRI images of the lungs and/or airways of a subject using a medical grade gas mixture comprises between about 20-79% inert perfluorinated gas and oxygen gas. The images are generated using acquired .sup.19F magnetic resonance image (MRI) signal data associated with the perfluorinated gas and oxygen mixture.

One aspect of the present subject matter provides an imaging method including: receiving a trigger signal; after a period substantially equal to a trigger delay minus an inversion delay, applying a non-selective inversion radiofrequency pulse to a region of interest followed by a slice-selective reinversion radiofrequency pulse to a slice of the region of interest of a subject; and after lapse of the trigger delay commenced at the cardiac cycle signal, acquiring a plurality of time-resolved images of the slice of the region of interest from an imaging device.

A universal, modular, temperature controlled MRI phantom for calibration and validation for anisotropic and isotropic imaging comprises an outer insulating shell configured to be received within an MRI chamber; an inner shell received within the outer insulating shell; a fluid conduits adjacent the inner shell for receiving temperature controlling fluid or gas cycling there-through; and a series of stacked layers of frames containing test points for the MRI phantom, each layer including at least one fiducial and including at least some anisotropic imaging test points in at least one frame and at least one isotropic imaging test point in at least one frame. The anisotropic imaging comprises hollow tubular textile fibers, wherein each hollow tubular fiber has an outer diameter of less than 50 microns and an inner diameter of less than 20 microns, wherein at least some hollow tubular fibers are filled with a fluid.

A method for correcting TOF MR data, including providing a coil sensitivity map for an examination region of an examination object, providing the TOF MR data of the examination region, and generating corrected TOF MR image data comprising multiplying the TOF MR data by an inverse of the coil sensitivity map.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for harmonizing diffusion tensor images. One of the methods includes obtaining a diffusion tensor image; determining a set of RISH features for the diffusion tensor image; processing a model input generated from the set of RISH features using a machine learning model to generate a model output identifying an image transformation from a set of image transformations, wherein each image transformation in the set of image transformations corresponds to a respective different first MRI scanner and represents a transformation that, when applied to first diffusion tensor images captured by the first MRI scanner, harmonizes the first diffusion tensor images with second diffusion tensor images captured by a reference MRI scanner; and processing the diffusion tensor image using the identified image transformation to generate a harmonized diffusion tensor image.

The present disclosure generally relate to a method and system for performing three-dimensional, 3D, magnetic resonance elastography, MRE. In particular, the present disclosure relates to a method and system for imaging an area of a patient using a multi-slice gradient echo, GRE, imaging sequence. Advantageously, the present techniques enable the four scans that are typically required to be performed during MRE, and during four breath-holds, to be combined into a single measurement that can be performed during a single breath-hold.