Systems and methods for reconstructing a motion-compensated magnetic resonance image are presented. In certain implementations, a computer-implemented method is provided. The method may include a plurality of operations, including receiving a set of k-space data from a magnetic resonance imaging device, dividing the set of k-space data into a plurality of groups, performing a plurality of initialization operations, performing a first iterative process until a first criteria for the first iterative process is achieved for a current scale of motion estimation, performing a second iterative process until a second criteria for the second iterative process is achieved, and outputting a motion-compensated magnetic resonance image reconstructed in accordance with a predetermined scale of motion estimation.

A magnetic resonance imaging apparatus according to an embodiment includes sequence control circuitry and processing circuitry. The sequence control circuitry executes a first pulse sequence and a second pulse sequence, the first pulse sequence including a first spoiler pulse serving as a dephasing gradient pulse of a first amount, the second pulse sequence including a second spoiler pulse serving as a dephasing gradient pulse of a second amount being different from the first amount or the second pulse sequence not including a spoiler pulse serving as a dephasing gradient pulse. The processing circuitry performs a subtraction operation between a first data obtained from the first pulse sequence and a second data obtained from the second pulse sequence, thereby generating an image.

Various systems and methods for generating images are provided. In some embodiments, the techniques can include acquiring a medical image and an associated motion characterization. The motion characterization can then be used to generate a plurality of gated image data sets, sorted by phase in the motion cycle. A new amplitude-based motion characterization curve is derived from the association of phases with amplitude-based characteristics in the phase gated images. This newly derived amplitude-based motion characterization curve can then be used to re-sort data according to amplitude-based gating techniques known in the field or with data driven optimization techniques.

Exemplary method, system and computer-accessible medium can be provided which facilitates an acquisition of radial data, which can be continuous, with an exemplary golden-angle procedure and reconstruction with arbitrary temporal resolution at arbitrary time points. According to such exemplary embodiment, such procedure can be performed with a combination of compressed sensing and parallel imaging to offer a significant improvement, for example in the reconstruction of highly undersampled data. It is also possible to provide an exemplary procedure for highly-accelerated dynamic magnetic resonance imaging using Golden-Angle radial sampling and multicoil compressed sensing reconstruction, called Golden-angle Radial Sparse Parallel MRI (GRASP).

Methods, devices, systems and apparatus for dynamic imaging based on echo planar imaging (EPI) sequence are provided. In one aspect, a method includes: obtaining first pre-scanned k-space data by performing a pre-scan for a subject based on a first EPI sequence and pre-scanning parameters, obtaining a pre-scanned image and second pre-scanned k-space data according to the first pre-scanned k-space data, performing a dynamic scan for the subject based on a second EPI sequence and dynamic scanning parameters to generate dynamically-scanned k-space data associated with each of a plurality of dynamic periods in the dynamic scan, and for each of the dynamic periods, generating a residual image according to the dynamically-scanned k-space data of the dynamic period and the second pre-scanned k-space data, and adding the pre-scanned image and the residual image to obtain a dynamic image of the dynamic period.

A system for performing inline measurements of flow rate, density, and rheology of a flowing fluid is disclosed, comprising: (a) a rheology measurement subsystem comprising: a horizontal tube of internal radius r.sub.H; means for measuring a velocity profile of a test fluid flowing through said horizontal tube at a distance x.sub.0 from its upstream end; and means for determining wall shear stress at a boundary between said flowing fluid and an inner surface of said horizontal tube; (b) a density measurement subsystem comprising: a vertical tube of internal radius r.sub.V in fluid connection with said horizontal tube; a pressure sensor for measuring the pressure of said test fluid within said vertical tube at a location y.sub.1; and, (c) a pressure sensor for measuring the pressure of said test fluid within said vertical tube at a location y.sub.2 downstream from y.sub.1 and displaced vertically from y.sub.1 by a distance h.

A system and method for reconstructing a series of images of a subject includes acquiring medical image data from the subject with a medical imaging system and reconstructing a series of images of the subject from the acquired medical image data set. The reconstructing includes enforcing general adherence to a non-patient-specific signal model that describes a dependency of image intensity values on at least one variable that is associated with a physical or physiological property by constraining reconstruction of individual images in the series of images using the non-patient-specific model. The reconstructing also includes preserving information in the series of images that deviate from the non-patient-specific model by controlling a requirement of consistency with the non-patient-specific model.

A method of processing magnetic resonance (MR) data of a sample under investigation, includes the steps of providing the MR data being collected with an MRI scanner apparatus, and subjecting the MR data to a multi-parameter nonlinear regression procedure being based on a non-linear MR model and employing a set of input parameters, wherein the regression procedure results in creating a parameter map of model parameters of the sample, wherein the input parameters (initial values and possibly boundaries) of the regression procedure are estimated by a machine learning based estimation procedure applied to the MR data. The machine learning based estimation procedure preferably includes at least one of at least one neural network and a support vector machine. Furthermore, an MRI scanner apparatus is described.

An MRI image processing and analysis system may identify instances of structure in MRI flow data, e.g., coherency, derive contours and/or clinical markers based on the identified structures. The system may be remotely located from one or more MRI acquisition systems, and perform: perform error detection and/or correction on MRI data sets (e.g., phase error correction, phase aliasing, signal unwrapping, and/or on other artifacts); segmentation; visualization of flow (e.g., velocity, arterial versus venous flow, shunts) superimposed on anatomical structure, quantification; verification; and/or generation of patient specific 4-D flow protocols. An asynchronous command and imaging pipeline allows remote image processing and analysis in a timely and secure manner even with complicated or large 4-D flow MRI data sets.

A method is provided for ascertaining at least one item of movement information describing a sought movement as a partial movement of an overall movement in an at least partially moved examination region. In the method, at least one excitation signal having a first frequency band is output and receiving signals generated by the excitation signal are recorded with a receiving coil arrangement, (e.g., a receiving coil arrangement of a magnetic resonance device), having a plurality of receiving channels. The coils of the receiving coil arrangement are designed to record a receiving frequency band including the first frequency band, wherein for ascertaining the movement information the complex receiving signals of the receiving channels are combined at one instant according to a combination specification ascertained over a period by an analysis of the receiving signals that identifies at least one component of a movement that contributes to the sought movement.