Deep learning techniques for generating magnetic resonance images from spatial frequency data
US11564590B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 12, 2020 |
| Grant date | Jan 31, 2023 |
| Priority date | — |
| Expiry date | Oct 7, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques include: obtaining input MR spatial frequency data obtained by imaging the subject using the MRI system; generating an MR image of the subject from the input MR spatial frequency data using a neural network model comprising: a pre-reconstruction neural network configured to process the input MR spatial frequency data; a reconstruction neural network configured to generate at least one initial image of the subject from output of the pre-reconstruction neural network; and a post-reconstruction neural network configured to generate the MR image of the subject from the at least one initial image of the subject.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.