A method for magnetic resonance imaging (MRI) may include obtaining a plurality of first magnetic resonance (MR) data sets related to a region of interest (ROI) of a subject. The plurality of first MR data sets may be collected based on two or more different values of a scan parameter. The method may also include determining a plurality of second MR data sets based on the plurality of first MR data sets. Each of the plurality of second MR data sets may correspond to at least two of the plurality of first MR data sets. The method may also include generate, based on the plurality of second MR data sets, a plurality of T1 weighted images of the ROI each of which corresponds to a target time point.

The present disclosure relates to a method and apparatus correcting a metal artifact in magnetic resonance imaging (MRI) data. The method and apparatus acquire plural slices along a slice direction of a scanned region associated with a body part, estimate a spatial extent of a signal dispersion of the acquired plural slices along the slice direction, and combine the signal of the acquired plural slices along the slice direction based on the estimated spatial extent of the signal dispersion to generate a reconstructed image of the scanned region. The method and apparatus may identify, from the acquired plural slices along the slice direction, a slice with a highest pixel intensity; and identify at least one neighboring slice neighboring the slice with the highest pixel intensity based on a 3D spatial dipole response function, wherein combining the signal of the acquired plural slices along the slice direction based on the estimated spatial extent of the signal dispersion comprises combining (a) the signal of the slice with the highest pixel intensity and (b) the signal of the at least one neighboring slice.

A method can include obtaining a scaling factor for a location proximate a metallic object by optimizing a function of an acquired dataset and a simulated dataset. The simulated dataset can include a first signal from a first pulse having a first excitation flip angle and a first refocusing flip angle. The simulated dataset can include a second signal from a second pulse having a second excitation flip angle and a second refocusing flip angle.

A method of performing magnetic resonance imaging of a body using a magnetic resonance imaging scanner the method includes applying to the body a time-varying magnetic field gradient (G.sub.x, G.sub.y, G.sub.z) defining a continuous trajectory (ST) in k-space complying with a set of constraints including constraints on maximum amplitude and maximum slew rate of the time-varying magnetic field gradient, such that sampling points (KS) belonging to the trajectory define a pseudo-random sampling of the k-space, approximating a predetermined target sampling density, the trajectory in k-space minimizing, subject to the set of constraints, a cost function defined by the difference between a first term, called attraction term, promoting consistency of the distribution of sampling points in k-space with the predetermined target sampling density, and a second term, called repulsion term, promoting separation in k-space between sampling points, the repulsion term being expressed as a sum of contributions corresponding to respective pairs of sampling points; wherein each the contribution is weighted by a weight which increase with temporal separation of the sampling points along the trajectory in k-space.

One or more example embodiments of the present invention relates to a method for generating a subject-specific map of a tissue property, in particular the magnetic susceptibility, of a region of interest within a subject, the method comprising receiving an MR image of the region of interest; inputting the MR image as input into at least one trained neural network, wherein the output of the neural network is an output image having improved contrast between bone and air; segmenting the output image into air and at least bone and at least one type of soft tissue to obtain a segmented image; and assigning pre-determined values for the tissue property to each category of tissue and air in the segmented image to obtain the subject-specific map of the tissue property.

Acquisition of MR data with a compressed sensing technique in a volume section includes ascertaining an extent of magnetic field distortion within the volume section. A first gradient along a first direction is switched. An RF excitation pulse is radiated for selective excitation of a slice in the volume section while the first gradient is switched. The MR data is acquired in a volume of the volume section that is composed of the slice, a partial volume above the slice, and a partial volume below the slice by executing the following multiple times: switching a first phase-encoding gradient along a second direction; switching a second phase-encoding gradient along the first direction; and reading out the MR data in a k-space line while a readout gradient is switched along a readout direction. A set of k-space lines to be read out for the volume is determined in dependence on the extent.

Quantitative susceptibility mapping methods, systems and computer-accessible medium include generating images of tissue magnetism property from complex magnetic resonance imaging data using the Bayesian inference approach. The tissue magnetism images is then used to monitor remyelination, such as remyelination in multiple sclerosis patients in response to therapy. Multiple sclerosis lesions defined on magnetic resonance imaging are further characterized on tissue magnetism images into hyperintense, isointense and hypointense parts for measuring remyelination. Thus, magnetic susceptibility information and other tissue properties associated with at least one structure are determined.

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.

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.

Magnetic susceptibility is calculated with high accuracy without significant increase of calculation time. Provided is an image processing device comprising an image processor for creating a susceptibility image representing a magnetic susceptibility of at least one tissue of the subject, from an image created on the basis of magnetic resonance signals generated from a subject, wherein the image processor includes an image separator configured to separate from the image, a specific tissue image representing a content of a predetermined specific tissue and a frequency image, an adder-subtractor configured to calculate a post-subtraction frequency image obtained by subtracting from the frequency image, frequency change caused by the specific tissue, and an image converter configured to calculate a specific susceptibility image representing the magnetic susceptibility of the specific tissue on the basis of the specific tissue image, and to calculate a post-subtraction susceptibility image on the basis of the post-subtraction frequency image.