Methods and systems for magnetic resonance image reconstruction using an extended sensitivity model and a deep neural network
US10712416B1 · kind B1 · utility
Assignees
Inventors
Key dates
| Filing date | Feb 5, 2019 |
| Grant date | Jul 14, 2020 |
| Priority date | — |
| Expiry date | Feb 5, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2211/424
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Various methods and systems are provided for reconstructing magnetic resonance images from accelerated magnetic resonance imaging (MRI) data. In one embodiment, a method for reconstructing a magnetic resonance (MR) image includes: estimating multiple sets of coil sensitivity maps from undersampled k-space data, the undersampled k-space data acquired by a multi-coil radio frequency (RF) receiver array; reconstructing multiple initial images using the undersampled k-space data and the estimated multiple sets of coil sensitivity maps; iteratively reconstructing, with a trained deep neural network, multiple images by using the initial images and the multiple sets of coil sensitivity maps to generate multiple final images, each of the multiple images corresponding to a different set of the multiple sets of sensitivity maps; and combining the multiple final images output from the trained deep neural network to generate the MR image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.