University of Minnesota

Siemens Healthcare Gmbh

Duke University

Steen Moeller

Michael G Garwood

Djaudat S Idiyatullin

Curtis A Corum

Mehmet Akcakaya

Kamil Ugurbil

Ryan Chamberlain

Pierre-Francois Van De Moortele

Carl J Snyder

Curt Corum

Can E Akgun

Edward Auerbach

John Thomas Vaughan

Vibhas S Deshpande

Guillermo Sapiro

J Thomas Vaughan, Jr

Gregor Adriany

Dingxin Wang

Gregory John Metzger

Sebastian Weingartner

Lance DelaBarre

Xiufeng Li

J Thomas Vaughan

Jinfeng Tian

Jang-Yeon Park

Essa Yacoub

Angela Lynn Styczynski Snyder

Noam Harel

Henry Braun

Tara Palnitkar

Seng-Wei Chieh

Oren Solomon

Sudhir Ramanna

Chi Zhang

Remi Patriat

Jr J Thomas Vaughan

A system and method are provided for creating magnetic resonance (MR) images with reduced motion artifacts from the MR data from which the images are produced. The method includes selecting a candidate image from a plurality of candidate images reconstructed from the MR data. The method also includes registering the candidate image to a reference image, comparing the candidate image to a consistency map, and, based on comparing the candidate image using the consistency map, selecting a blending algorithm. The method also includes generating a blended image using the blending algorithm and the candidate image and repeating these steps for each candidate image. The method also includes performing a Fourier aggregation to generate a combined image and displaying the combined image with reduced motion artifacts compared to the plurality of candidate images.

System and method for control of motion in medical images using aggregation

Images are reconstructed from undersampled k-space data using a residual machine learning algorithm (e.g., a ResNet architecture) to estimate missing k-space lines from acquired k-space data with improved noise resilience. Using a residual machine learning algorithm provides for combining the advantages of both linear and nonlinear k-space reconstructions. The linear residual connection can implement a convolution that estimates most of the energy in k-space, and the multi-layer machine learning algorithm can be implemented with nonlinear activation functions to estimate imperfections, such as noise amplification due to coil geometry, that arise from the linear component.

Methods for scan-specific artifact reduction in accelerated magnetic resonance imaging using residual machine learning algorithms

Methods for reconstructing images from undersampled k-space data using a machine learning approach to learn non-linear mapping functions from acquired k-space lines to generate unacquired target points across multiple coils are described.

Methods for scan-specific k-space interpolation reconstruction in magnetic resonance imaging using machine learning

Magnetic resonance imaging ('MRI') data are corrected from corruptions due to physiological changes using a self-navigated phase correction technique. Unlike motion correction techniques, the effects of physiological changes (e.g., breathing and respiration) are corrected by making the MRI data self-consistent relative to an absolute uncorrupted phase reference. This phase correction information can be extracted from the acquisition itself, thereby eliminating the need for a separate navigator scan, and establishing an accelerated acquisition. This absolute reference can be computed in a data segmented space, and the subsequent data can be corrected relative to this absolute reference with low-resolution phases.

Efficient multi-shot EPI with self-navigated segmentation

A fully sampled calibration data set, which may be Cartesian k-space data, is used to obtain targeted and optimal interpolation kernels for non-regularly sampled data. The calibration data are self-calibration data obtained from a time-averaged image, or re-sampled data. ACS data are resampled for calibration of region-specific kernels. Subsequently, an explicit noise-based regularized solution can be utilized to estimate region-specific kernels for reconstruction.

Scalable self-calibrated interpolation of undersampled magnetic resonance imaging data

Described here are systems and methods for volumetric excitation in magnetic resonance imaging ('MRI') using frequency modulated radio frequency ('RF') pulses. In general, quadratic phase modulation along the slice encoding direction is implemented for additional spatiotemporal encoding, which better distributes signal content in the slice direction and enables higher acceleration rates that are robust to slice-undersampling.

Method for magnetic resonance imaging using slice quadratic phase for spatiotemporal encoding

Methods for fast magnetic resonance imaging ('MRI') using a combination of outer volume suppression ('OVS') and accelerated imaging, which may include simultaneous multislice (&#x201c;SMS&#x201d;) imaging, data acquisitions amenable to compressed sensing reconstructions, or combinations thereof. The methods described here do not introduce fold-over artifacts that are otherwise common to reduced field-of-view (&#x201c;FOV&#x201d;) techniques.

Methods and apparatus for scan time reductions in magnetic resonance imaging using outer volume supression

A system and method for controlling noise in magnetic resonance imaging (MRI) are provided. In one aspect, the method includes reconstructing a series of images of the target using the image data, with each image being defined using signal-to-noise (SNR) units, and selecting an image patch corresponding to the series of images. The method also includes forming a matrix by combining vectors generated using the image patch, and applying a local low rank denoising technique using the matrix and the series of images to generate at least one denoised image.

System and method for controlling noise in magnetic resonance imaging using a local low rank technique

A method for generating a magnetic resonance image includes applying a radio frequency (RF) pulse to a specimen. The method includes modulating a spatially varying magnetic field to impart an angular velocity to a trajectory of a region of resonance relative to the specimen. The method includes acquiring data corresponding to the region of resonance and reconstructing a representation of the specimen based on the data.

Steering resonance along a trajectory

A system includes a data receiver, a sinogram generator, a processor, a filter module, and an output module. The data receiver is configured to receive radial ordered magnetic resonance data. The sinogram generator is configured to generate a first sinogram corresponding to a view angle as a function of a readout direction for the magnetic resonance data. The processor is configured to generate an oscillogram having an angular frequency axis. The oscillogram corresponds to a Fourier transform of the first sinogram. The filter module is configured to selectively filter a peak in a projection formed along a selected axis of the oscillogram, the peak being related to an interference signal such as an RF interference. The selected axis is orthogonal to the angular frequency axis. The output module is configured to form a second sinogram corresponding to a transform of the filtered projection.

Method of oscillogram filtering for radial MRI data

A magnetic resonance method and system are provided for providing improved multi-band (MB) magnetic resonance imaging. The adaptive MB imaging can be achieved by providing one or more modified multi-band excitation pulse sequences that include at least either one nullified 'dummy' slice within a slab that is not excited simultaneously with the other slices during a single multislice acquisition sequence, or one excitation slice group that utilizes a non-uniform slice spacing between simultaneously excited slices. Adaptive GRAPPA or slice-GRAPPA kernel sizes can also be used during image reconstruction to improve speed without excessive point spread blurring or MB reconstruction failure. A total leakage factor (TLF) can also be determined based on test images using modified MB excitation sequences, and used to improve the adaptive MB procedure.

Apparatus and method for multi-band MR imaging

A method includes applying a pulse train to a spin system in a scanner. The pulse train has a plurality of discontinuities in a time domain. The method includes receiving a response from the spin system. The response corresponds to a gated signal. The method includes accessing a correction factor corresponding to the scanner. The method includes calculating a correction to the response based on the correction factor. The method includes generating an output based on the correction.

Sideband processing for magnetic resonance

Positive contrast localization of magnetic (e.g. superparamagnetic) particles in vivo or in vitro by means of SWIFT-MRI using the imaginary component of MR image data in combination with an anatomic reference image derived from the real or magnitude component.

Localization of magnetic particles by means of swift-MRI

A method for iteratively calibrating a reconstruction kernel for use in accelerated magnetic resonance imaging (MRI) is provided. An MRI system is used to acquire k-space data from multiple slice locations following the application of a multiband radio frequency (RF) excitation pulse. An initial reconstruction kernel is generated from the acquired k-space data, and this initial reconstruction kernel is used to produce an initial image for each of the multiple slice locations by applying the initial reconstruction kernel to the acquired k-space data. The average phase of each slice location is then calculated from these images, and used to shift the phase values of the subsequently acquired k-space data. From the phase-shifted k-space data, an updated reconstruction kernel is then generated. This process is repeated iteratively until a stopping criterion is satisfied.

System and method for iteratively calibrated reconstruction kernel for accelerated magnetic resonance imaging

A method for magnetic resonance imaging includes providing a radio frequency excitation pulse to a specimen. The pulse has a duration. The method includes, concurrent with providing the radio frequency excitation pulse, applying a first gradient having a first polarity. The method includes applying a readout gradient at a time after the duration. The readout gradient has inverse polarity relative to the first polarity. The method includes, concurrent with applying the readout gradient, acquiring magnetic resonance data from the specimen. The method includes generating an image based on the magnetic resonance data.

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Steen Moeller