General Electric Company

Ek Tsoon Tan

Christopher Judson Hardy

Luca Marinelli

Thomas Kwok-Fah Foo

Jonathan Immanuel Sperl

Marion Irene Menzel

Kevin Franklin King

Xiaofeng Liu

John F Schenck

Albert Amos Montillo

Mark Ernest Vermilyea

Dan Xu

Robert Marc Lebel

Vincent B Ho

Prem Venugopal

Eric William Fiveland

Zachary Slavens

Yihe Hua

Dominic Michael Graziani

Christina Margaret Vasil

Anja Christina Sophie Brau

Stephen Joseph Garnier

Justin Michael Ricci

Giang-Chau Ngo

The techniques discussed herein relate to a reduced acoustic noise and vibration magnetic resonance imaging (MRI) acquisition. In certain implementations acoustic noise levels for one or more MRI pulse sequences are characterized and modified by limiting the frequencies and amplitudes of the gradient waveforms so as to produce less noise and vibration when the modified waveform is used during an MRI examination. In this manner, relatively low sound pressure levels can be attained.

Low acoustic noise magnetic resonance image acquisition

An imaging device may include a patient bore to house a subject to be imaged, wherein the patient bore includes one or more bore tubes. The imaging device may also include a gradient coil surrounding, at least partially, the patient bore and a radio frequency (RF) shield located outside the one or more bore tubes. Additionally, the imaging device may include an RF coil located within at least one of the bore tubes.

Radiofrequency coil and shield in magnetic resonance imaging method and apparatus

A magnetic resonance (MR) imaging method performed by an MR imaging system includes acquiring MR data in multiple shots and multiple acquisitions (NEX), separately reconstructing the component magnitude and phase of images corresponding to the multiple shots and multiple NEX, removing the respective phase from each of the images, and combining, after removal of the respective phase, the shot images and the NEX images to produce a combined image. The method further includes using the combined image to calculate the full k-space data for each shot and NEX and replacing unacquired k-space data points with calculated k-space data points. The operations are repeated until the combined image reaches a convergence.

Method and systems for iteratively reconstructing multi-shot, multi-acquisition MRI data

A method for determining an arterial pulse wave velocity representative of a health condition of a blood vessel includes receiving an image data set comprising a plurality of images of a subject, from an imaging modality. The method also involves determining a blood vessel region in an image from the plurality of images. The method further includes determining a plurality of cross-sectional area values of a blood vessel at a plurality of locations in the blood vessel region, corresponding to a plurality of phases of a cardiac cycle of the subject and determining a plurality of flow rate values of blood flowing in the blood vessel corresponding to the plurality of cross-sectional area values. The method also includes determining a hemodynamic model based on the plurality of cross-sectional area values and the plurality of blood flow rate values and determining the arterial pulse wave velocity based on the hemodynamic model.

System and method for estimating arterial pulse wave velocity

A magnetic resonance imaging method includes generating spatially resolved fiber orientation distributions (FODs) from magnetic resonance signals acquired from a patient tissue using a plurality of diffusion encodings, each acquired magnetic resonance signal corresponding to one of the diffusion encodings and being representative of a three-dimensional distribution of displacement of magnetic spins of gyromagnetic nuclei present in each imaging voxel. Generating the spatially resolved FODs includes performing generalized spherical deconvolution using the acquired magnetic resonance signals and a modeled tissue response matrix (TRM) to reconstruct the spatially resolved FODs. The method also includes using the spatially resolved FODs to generate a representation of fibrous tissue within the patient tissue.

Generalized spherical deconvolution in diffusion magnetic resonance imaging

A method implemented using at least one processor includes receiving a target image and a reference image. The target image is a distorted magnetic resonance image and the reference image is an undistorted magnetic resonance image. The method further includes selecting an image registration method for registering the target image to the reference image, wherein the image registration method uses an image transformation. The method further includes performing image registration of the target image with the reference image, wherein the image registration provides a plurality of optimized parameters of the image transformation. The method also includes generating a corrected image based on the target image and the plurality of optimized parameters of the image transformation.

System and method for medical image correction

Systems and methods for correcting magnetic resonance (MR) data are provided. One method includes receiving the MR data and correcting errors present in the MR data due to non-uniformities in magnetic field gradients used to generate the diffusion weighted MR signals. The method also includes correcting errors present in the MR data due to concomitant gradient fields present in the magnetic field gradients by using one or more gradient terms. At least one of the gradient terms is corrected based on the correction of errors present in the MR data due to the non-uniformities in the magnetic field gradients.

Magnetic resonance imaging data correction methods and systems

Systems and methods for generating a magnetic resonance (MR) image of a tissue are provided. A method includes acquiring MR raw data. The MR raw data corresponds to MR signals obtained at undersampled q-space locations for a plurality of q-space locations that is less than an entirety of the q-space locations and the MR signals at the q-space locations represent the three dimensional displacement distribution of the spins in the imaging voxel. The method also includes performing a joint image reconstruction technique on the MR raw data to exploit structural correlations in the MR signals to obtain a series of accelerated MR images and performing, for each image pixel in each accelerated MR image of the series of accelerated MR images, a compressed sensing reconstruction technique to exploit q-space signal sparsity to identify a plurality of diffusion maps.

Diffusion spectrum imaging systems and methods

A system and method of self-calibrated correction for residual phase in phase-contrast magnetic resonance (PCMR) imaging data. The method includes receiving PCMR image data from an MR scanner system, segmenting static tissue from non-static cardiovascular elements of the image data, calculating a non-linear fitted-phase basis function, the non-linear fitted-phase basis function based on system artifacts of the PCMR system, adding the non-linear fitted-phase basis function to linear fit terms, and subtracting the result of the adding step from the PCMR imaging data. The system includes a PCMR scanning apparatus configured to provide PCMR image data, a scanner control circuit configured to control the scanning apparatus during image acquisition, the scanner control circuitry in communication with a control processor, the control processor configured to execute computer-readable instructions that cause the control processor to perform the method. A non-transitory computer-readable medium is also disclosed.

Systems and methods for self-calibrated, nonlinear phase contrast correction of magnetic resonance images

The system and method of the invention combines target image intensity into a maximum likelihood estimate (MLE) framework as in STAPLE to take advantage of both intensity-based segmentation and statistical label fusion based on atlas consensus and performance level, abbreviated iSTAPLE. The MLE framework is then solved using a modified expectation-maximization algorithm to simultaneously estimate the intensity profiles of structures of interest as well as the true segmentation and atlas performance level. The iSTAPLE greatly extends the use of atlases such that the target image need not have the same image contrast and intensity range as the atlas images.

Systems and methods for image segmentation using target image intensity

A method for measuring diffusional anisotropy in diffusion-weighted magnetic resonance imaging. The method includes determining an orientation diffusion function (ODF) for one or more fibers within a single voxel, wherein the ODF includes lobes representative of a probability of diffusion in a given direction for the one or more fibers. The method also includes characterizing an aspect ratio of the lobes. The method further includes determining a multi-directional anisotropy metric for the one or more fibers based on the aspect ratio of the lobes.

Measuring diffusional anisotropy of ODF lobes having maxima peaks and minima troughs with diffusion weighted MRI

A method of compressed sensing for multi-shell magnetic resonance imaging includes obtaining magnetic resonance imaging data, the data being sampled along multi-shell spherical coordinates, the spherical coordinates coincident with a plurality of spokes that converge at an origin, constructing a symmetric shell for each respective sampled multi-shell to create a combined set of data, performing a three-dimensional Fourier transform on the combined set of data to reconstruct an image, and de-noising the reconstructed image by iteratively applying a sparsifying transform on non-sampled data points of neighboring shells. The method can also include randomly under-sampling the imaging data to create missing data points. A system configured to implement the method and a non-transitory computer readable medium are also disclosed.

Systems and methods for compressed sensing for multi-shell magnetic resonance imaging

Systems and methods for image segmentation using a deformable atlas are provided. One method includes obtaining one or more target images, obtaining one or more propagated label probabilities for the one or more target images, and segmenting the one or more target images using a cost function of a deformable atlas model. The method further includes identifying segmented structures within the one or more target images based on the segmented one or more target images.

Systems and methods for image segmentation using a deformable atlas

Systems and methods for Magnetic Resonance Angiography (MRI) are provided. One method includes obtaining Magnetic Resonance (MR) velocity data and determining a distance map for one or more vessels to define a distance path. The method also includes calculating, using the MR velocity data, at a plurality of time intervals and for a plurality of pixels (i) a distance traveled during a current time interval as a current distance traveled, wherein a total distance traveled is incremented by the current distance traveled and (ii) a bolus signal using a bolus signal profile, the distance path and total distance traveled, wherein a current time interval is incremented by a defined time step.

Systems and methods for magnetic resonance angiography

A magnetic resonance (MR) imaging method includes acquiring MR signals having phase and magnitude at q-space locations using a diffusion sensitizing pulse sequence performed on a tissue of interest, wherein the acquired signals each include a set of complex Fourier encodings representing a three-dimensional displacement distribution of the spins in a q-space location. The signals each include information relating to coherent motion and incoherent motion in the q-space location. The method also includes determining a contribution by coherent motion to the phase of the acquired MR signals; removing the phase contribution attributable to coherent motion from the acquired MR signals to produce a complex data set for each q-space location and an image of velocity components for each q-space location; and producing a three-dimensional velocity image from the image of the velocity components.

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Mechanicville, NY, United States of America

Ek Tsoon Tan