Deep learning techniques for magnetic resonance image reconstruction
US12181553B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 23, 2022 |
| Grant date | Dec 31, 2024 |
| Priority date | — |
| Expiry date | Mar 23, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.