Abstract: Images are reconstructed from k-space acquired with a magnetic resonance imaging (“MRI”) system using a multi-shot pulse sequence. In each iteration, a phase-aware image reconstruction, a data-consistency update across all shots or subsets of data, and a relative phase estimation across the reconstructed images for each shot are performed. In this way. the reconstruction framework recasts the problem as an iterative relative phase estimation problem, which allows for the use relative phase estimation techniques. Through an iterative search, an artifact-free combined image and the smooth relative phase between each shot in the multi-shot k-space data can be jointly estimated.

Abstract: A combined physics-based and machine learning framework is used for reconstructing images from k-space data, in which motion artifacts are significantly reduced in the reconstructed images. In general, model-based retrospective motion correction techniques are accelerated using fast machine learning (“ML”) steps, which may be implemented using a trained neural network such as a convolutional neural network. In this way, the confidence of a classical physics-based reconstruction is obtained with the computational benefits of an ML-based network.

Abstract: A method for determining peripheral nerve stimulation during MR imaging of a patient in a MR scan unit for a MR pulse sequence is described. In the method, a plurality of model-based candidate stimulations are determined dependent on a unit vector potential of the gradient magnet field generated during MR imaging and dependent on candidate data models for different object parameter values. A model-based candidate data stimulation is selected as a stimulation model for the patient dependent on an individual patient model. A distribution of a vector potential of a gradient magnetic field acting on the patient is determined as a function of a unit gradient current for a determined position of the patient in the MR scanning unit. The nerve stimulation of the patient is determined for the determined position based on the selected candidate stimulation and a gradient current of a gradient pulse of the MR pulse sequence.

Abstract: A system and method is provided for assessing Peripheral Nerve Stimulation (PNS). The system receives an imaging pulse sequence to be applied to a region of interest (ROI) of a subject arranged in the imaging system, where the imaging pulse sequence identifies coil parameters related to at least one coil. The system obtains a first model including a plurality of tissue types and corresponding electromagnetic properties in the ROI. The system then obtains a second model indicating location, orientation, and/or physiological properties of one or more nerve tracks in the ROI. The system estimates a plurality of PNS thresholds in the ROI caused by the imaging pulse sequence applied in the imaging system using the first model, the second model, a nerve membrane model, and the coil parameters.

Abstract: Techniques are disclosed related to increasing prior limits imposed on MR gradient switching speed (dB/dt) without causing significant discomfort or severe pain perception to patients. The technique disclosed herein do so by modifying the pulsing gradient fields that are ordinarily available for MR imaging protocols. Doing so stimulates the peripheral nerves and thus enables a quick, reversible, and complete inhibition of action potential propagation through the stimulated region of tissue, referred to as a nerve conduction block.

Abstract: A method for determining peripheral nerve stimulation during MR imaging of a patient in a MR scan unit for a MR pulse sequence is described. In the method, a plurality of model-based candidate stimulations are determined dependent on a unit vector potential of the gradient magnet field generated during MR imaging and dependent on candidate data models for different object parameter values. A model-based candidate data stimulation is selected as a stimulation model for the patient dependent on an individual patient model. A distribution of a vector potential of a gradient magnetic field acting on the patient is determined as a function of a unit gradient current for a determined position of the patient in the MR scanning unit. The nerve stimulation of the patient is determined for the determined position based on the selected candidate stimulation and a gradient current of a gradient pulse of the MR pulse sequence.

Abstract: A combined physics-based and machine learning framework is used for reconstructing images from k-space data, in which motion artifacts are significantly reduced in the reconstructed images. In general, model-based retrospective motion correction techniques are accelerated using fast machine learning (“ML”) steps, which may be implemented using a trained neural network such as a convolutional neural network. In this way, the confidence of a classical physics-based reconstruction is obtained with the computational benefits of an ML-based network.

Abstract: Systems and methods for reconstructing MR parameter maps of a subject from magnetic resonance fingerprinting (MRF) data acquired using a magnetic resonance imaging (MRI) system. The method includes providing MRF data acquired from a subject using an MRI system and reconstructing the MRF data by solving a constrained optimization problem using a low-rank model, for which an input to the optimization problem is the MRF data and an output from the optimization problem is the MRF time-series images.

Abstract: Described here are systems and methods for producing images of a subject using magnetic resonance imaging (“MRI”) in which data are acquired using a sparse approximate encoding scheme for controlled aliasing techniques. As one example, the sparse approximate encoding can be used for a Wave-CAIPI encoding scheme, which can enable faster image reconstruction using fewer computational resources, in addition to reducing noise in the reconstructed images relative to those reconstructed from data acquired using a Wave-CAIPI encoding scheme without sparse approximate encoding.

Abstract: Methods for reducing scan time in magnetic resonance imaging (“MRI”), particularly when imaging three-dimensional image volumes, using a simultaneous time-interleaved multislice (“STIMS”) acquisition are described. The unused time in each repetition time (“TR”) period is exploited to provide an additional reduction in encoding time for a three-dimensional acquisition (e.g., a 3D whole brain coverage). Groups of spatially interleaved slices are excited in a single TR, with the excitation and acquisition of the groups of slices being interleaved in time.

Abstract: Techniques are disclosed related to increasing prior limits imposed on MR gradient switching speed (dB/dt) without causing significant discomfort or severe pain perception to patients. The technique disclosed herein do so by modifying the pulsing gradient fields that are ordinarily available for MR imaging protocols. Doing so stimulates the peripheral nerves and thus enables a quick, reversible, and complete inhibition of action potential propagation through the stimulated region of tissue, referred to as a nerve conduction block.

Abstract: Systems and methods for performing diffusion-weighted magnetic resonance imaging (“MRI”), including reconstructing and analyzing images, while preserving phase information that is traditionally discarded in such applications, are provided. For instance, background phase variations are eliminated, which enables complex-valued data analysis without the usual noise bias. As a result, the systems and methods described here provide an image reconstruction that enables true signal averaging, which increases signal-to-noise ratio (“SNR”) and allows higher contrast in diffusion model reconstructions without a magnitude bias.

Abstract: Described here are systems and methods for producing images of a subject using magnetic resonance imaging (“MRI”) in which data are acquired using a sparse approximate encoding scheme for controlled aliasing techniques. As one example, the sparse approximate encoding can be used for a Wave-CAIPI encoding scheme, which can enable faster image reconstruction using fewer computational resources, in addition to reducing noise in the reconstructed images relative to those reconstructed from data acquired using a Wave-CAIPI encoding scheme without sparse approximate encoding.

Abstract: Systems and methods for a hierarchical mapping framework (“HMF”} for coil compression are provided. The HMF-based coil compression can be applied to existing coil compression algorithms to improve their performance. The receive channels associated with a coil array are divided into subgroups based on the strength of their mutual correlation. In each subgroup, one or more virtual channels are produced based on the channels not in the subgroup. The virtual channels are produced using a coil compression algorithm subject to a hierarchically semiseparable channel mixing across the subgroups. Images are reconstructed for the subgroups and then combined to produce the final image of the subject.

Abstract: A method of determining a decoupling matrix of a decoupling system for an array of coils of a parallel transmission magnetic resonance imaging (MRI) system includes obtaining impedance matrix data for the array of coils without the decoupling system, determining, based on the impedance matrix data for the array of coils, an objective function representative of deviation from a decoupled operating condition for the array of coils in which the array of coils are decoupled via the decoupling system, and defining, with a processor, a decoupling matrix representative of a set of impedances of the decoupling system with an iterative procedure that optimizes elements of the decoupling matrix to minimize the objective function and reach the decoupled operating condition.

Abstract: A system and method for magnetic resonance imaging (MRI) and static field (B0) shimming. A coil system includes a conductive loop configured to be arranged proximate to a region of interest (ROI). The coil system also includes an alternating current (AC) circuit electrically connecting the conductive loop to an AC electrical connection configured to be coupled to an MRI system to communicate medical imaging signals received by the conductive loop from the ROI during a medical imaging procedure to the MRI system. The coil system further includes a direct current (DC) circuit electrically connecting the conductive loop to a DC electrical connection configured to be coupled to a DC power source and a plurality of circuit components configured to block DC signals from reaching the AC electrical connection in order to produce a spatially varying static magnetic field for shimming inhomogenieties of the static field.

Abstract: Systems and methods for acquiring magnetic resonance fingerprinting (MRF) imaging data from a subject using a magnetic resonance imaging (MRI) system are provided. The method includes receiving an indication of an MRF imaging process to be performed by the MRI system and receiving a desired design objective for the MRF imaging process and a configuration metric associated with the MRF imaging process. The method further includes using the configuration metric to bound a variance of tissue parameter estimates associated with the MRF imaging process and determine imaging parameters that achieve the desired design objective. The method also includes performing the MRF imaging process using the determined imaging parameters to acquire MRF data using the MRI system.

Abstract: Systems and methods for reconstructing magnetic resonance (MR) tissue parameter maps of a subject from magnetic resonance fingerprinting (MRF) data acquired using a magnetic resonance imaging (MRI) system. The method includes providing MRF data acquired from a subject using an MRI system and performing an iterative, maximum-likelihood reconstruction of the MRF data to create MR tissue parameter maps of the subject.

Abstract: A magnetic resonance imaging (MRI) system includes a plurality of transmitters to generate a parallel transmission radio frequency (RF) pulse, an array of coils coupled to the plurality of transmitters to apply the parallel transmission RF pulse to a subject, and a decoupling system connected to the plurality of transmitters and the array of coils. The decoupling system includes a plurality of hybrid couplers, each hybrid coupler of the plurality of hybrid couplers being coupled to a respective pair of the plurality of transmitters and to a respective pair of the array of coils. The plurality of hybrid couplers are configured to diagonalize an impedance matrix of the plurality of coils.

Abstract: Systems and methods for reconstructing images using a hierarchically semiseparable (“HSS”) solver to compactly represent the inverse encoding matrix used in the reconstruction are provided. The reconstruction method includes solving for the actual inverse of the encoding matrix using a direct (i.e., non-iterative) HSS solver. This approach is contrary to conventional reconstruction methods that repetitively evaluate forward models (e.g., compressed sensing or parallel imaging forward models).