DEEP LEARNING TECHNIQUES FOR MAGNETIC RESONANCE IMAGE RECONSTRUCTION

• Main Authors: SOFKA, Michal, DYVORNE, Hadrien, A, ROTHBERG, Jonathan, M, LAZARUS, Carole, KUNDU, Prantik, MOSHEN SALEHI, Seyed, Sadegh, O'HALLORAN, Rafael, SACOLICK, Laura, WANG, Ziyi, SCHLEMPER, Jo
• Format: Patent
• Language: English; French; German
• Published: 09.06.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DIAGNOSIS; HUMAN NECESSITIES; HYGIENE; IDENTIFICATION; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; MEASURING; MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES; MEDICAL OR VETERINARY SCIENCE; PHYSICS; SURGERY; TESTING

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.