DEEP LEARNING TECHNIQUES FOR MAGNETIC RESONANCE IMAGE RECONSTRUCTION

A magnetic resonance imaging (MRI) system, comprising: a magnetics system comprising: a B0 magnet configured to provide a B0 field for the MRI system; gradient coils configured to provide gradient fields for the MRI system; and at least one RF coil configured to detect magnetic resonance (MR) signal...

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Bibliographic Details
Main Authors Lazarus, Carole, Sacolick, Laura, Wang, Ziyi, Rothberg, Jonathan M, Schlemper, Jo, Dyvorne, Hadrien A, O'Halloran, Rafael, Sofka, Michal, Moshen Salehi, Seyed Sadegh, Kundu, Prantik
Format Patent
LanguageEnglish
Published 30.01.2020
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
MEASURING
MEASURING ELECTRIC VARIABLES
MEASURING MAGNETIC VARIABLES
PHYSICS
TESTING
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Summary:A magnetic resonance imaging (MRI) system, comprising: a magnetics system comprising: a B0 magnet configured to provide a B0 field for the MRI system; gradient coils configured to provide gradient fields for the MRI system; and at least one RF coil configured to detect magnetic resonance (MR) signals; and a controller configured to: control the magnetics system to acquire MR spatial frequency data using non-Cartesian sampling; and generate an MR image from the acquired MR spatial frequency data using a neural network model comprising one or more neural network blocks including a first neural network block, wherein the first neural network block is configured to perform data consistency processing using a non-uniform Fourier transformation.
Bibliography:Application Number: US201916524598