The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 31, 2024

Filed:

Mar. 23, 2022
Applicant:

Hyperfine Operations, Inc., Guilford, CT (US);

Inventors:

Jo Schlemper, Long Island City, NY (US);

Seyed Sadegh Mohseni Salehi, Bloomfield, NJ (US);

Michal Sofka, Princeton, NJ (US);

Prantik Kundu, Branford, CT (US);

Ziyi Wang, Durham, NC (US);

Carole Lazarus, Paris, FR;

Hadrien A. Dyvorne, New York, NY (US);

Laura Sacolick, Guilford, CT (US);

Rafael O'Halloran, Guilford, CT (US);

Jonathan M. Rothberg, Miami Beach, FL (US);

Assignee:

Hyperfine Operations, Inc., Guilford, CT (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01R 33/56 (2006.01); G01R 33/561 (2006.01); G06F 17/14 (2006.01); G06F 17/18 (2006.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06T 11/00 (2006.01); G06V 10/44 (2022.01); G06V 10/70 (2022.01); G06V 10/764 (2022.01);
U.S. Cl.
CPC ...
G01R 33/5608 (2013.01); G01R 33/561 (2013.01); G06F 17/142 (2013.01); G06F 17/18 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06T 11/006 (2013.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/768 (2022.01); G06T 2210/41 (2013.01);
Abstract

A magnetic resonance imaging (MRI) system, comprising: a magnetics system comprising: a Bmagnet configured to provide a Bfield 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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