General Electric Company

Ge Precision Healthcare LLC

Ling Sun

Wei Sun

Dawei Gui

Shaorong Chang

Zachary Slavens

Charles Robert Michelich

Anand Kumar Venkatachari

Anja Kammeier

Dashen Chu

Xiaoli Zhao

Eric M Printz

Haonan Wang

Brent Robinson

Various methods and systems are provided for correcting transmit attenuation of an amplifier of a transmit radio frequency (RF) coil for use in a magnetic resonance imaging (MRI) system. In one example, a method includes setting a reference value of transmit attenuation for an amplifier of a transmit radio frequency (RF) coil, acquiring a three-dimensional Bfield map with the transmit attenuation set at the reference value, determining a plurality of mean flip angles for a plurality of slice locations in a pre-scan imaging volume from the Bfield map, determining a transmit attenuation correction value for each of the slice locations based on a prescribed flip angle and the mean flip angle determined for the respective slice location, correcting the reference value of transmit attenuation with the transmit attenuation correction value at each of the slice locations to obtain a final value of transmit attenuation for each of the slice locations, and performing an MRI scan with the transmit attenuation set at the value.

Methods and systems for estimating transmit attenuation for a magnetic resonance imaging scan

Various methods and systems are provided for correcting transmit attenuation of an amplifier of a transmit radio frequency (RF) coil for use in a magnetic resonance imaging (MRI) system. In one example, a method includes setting a reference value of transmit attenuation for an amplifier of a transmit radio frequency (RF) coil, acquiring a two-dimensional Bfield map with the transmit attenuation set at the reference value, determining a mean flip angle from the Bfield map, determining a transmit attenuation correction value based on a prescribed flip angle and the mean flip angle, correcting the reference value of transmit attenuation with the transmit attenuation correction value to obtain a final value of transmit attenuation, and performing an MRI scan with the transmit attenuation set at the value.

Methods and systems are provided for predicting Bfield maps from magnetic resonance calibration images using deep neural networks. In an exemplary embodiment a method for magnetic resonance imaging comprises, acquiring a magnetic resonance (MR) calibration image of an anatomical region, mapping the MR calibration image to a transmit field map (Bfield map) with a trained deep neural network, acquiring a diagnostic MR image of the anatomical region, and correcting inhomogeneities of a transmit field in the diagnostic MR image with the Bfield map. Further, methods and systems are provided for collecting and processing training data, as well as utilizing the training data to train a deep learning network to predict Bfield maps from MR calibration images.

Systems and methods for predicting Bmaps from magnetic resonance calibration images

Various methods and systems are provided for selecting radio frequency (RF) coil array for magnetic resonance imaging (MRI). In one embodiment, the method comprises grouping the plurality of coil elements into receiving elements groups (REGs) according to REGs information, generating channel sensitivity maps for the plurality of coil elements, generating REG sensitivity maps based on the REGs information and the channel sensitivity maps, selecting one or more REGs based on the REG sensitivity maps and a region of interest (ROI), and scanning the ROI with the coil elements of the one or more selected REGs being activated and the coil elements not in any selected REGs being deactivated. In this way, coil arrays may be automatically selected for improved image quality of the MRI.

Methods and systems for coil selection in magnetic resonance imaging

Various methods and systems are provided for selecting coil elements of a plurality of coil elements of a radio frequency (RF) coil array for use in a magnetic resonance imaging (MRI) system. In one example, a method includes grouping the plurality of coil elements into receive elements groups (REGs) according to REGs information, generating channel sensitivity maps for the plurality of coil elements, generating REG sensitivity maps based on the REGs information and the channel sensitivity maps, labeling each REG as either selectable or not selectable based on the REG sensitivity maps, selecting one or more REGs from the selectable REGs based on the REG sensitivity maps and a region of interest (ROI), and scanning the ROI with the coil elements in the one or more selected REGs being activated and the coil elements not in any selected the other REGs being deactivated.

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Brookfield, WI, United States of America

Ling Sun