- 专利标题: DEEP LEARNING TECHNIQUES FOR MAGNETIC RESONANCE IMAGE RECONSTRUCTION
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申请号: US16524598申请日: 2019-07-29
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公开(公告)号: US20200034998A1公开(公告)日: 2020-01-30
- 发明人: Jo Schlemper , Seyed Sadegh Moshen Salehi , Michal Sofka , Prantik Kundu , Ziyi Wang , Carole Lazarus , Hadrien A. Dyvorne , Laura Sacolick , Rafael O'Halloran , Jonathan M. Rothberg
- 申请人: Jo Schlemper , Seyed Sadegh Moshen Salehi , Michal Sofka , Prantik Kundu , Ziyi Wang , Carole Lazarus , Hadrien A. Dyvorne , Laura Sacolick , Rafael O'Halloran , Jonathan M. Rothberg
- 主分类号: G06T11/00
- IPC分类号: G06T11/00 ; G06N3/04 ; G06N3/08 ; G06F17/14 ; G01R33/56 ; G01R33/561
摘要:
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.
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IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06T | 一般的图像数据处理或产生 |
G06T11/00 | 2D〔二维〕图像的生成 |