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. 09, 2025

Filed:

Mar. 24, 2021
Applicant:

Koninklijke Philips N.v., Eindhoven, NL;

Inventors:

Kay Nehrke, Hamburg, DE;

Peter Boernert, Hamburg, DE;

Assignee:

Koninklijke Philips N.V., Eindhoven, NL;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01R 33/565 (2006.01); G01R 33/48 (2006.01); G01R 33/56 (2006.01); G06N 3/08 (2023.01);
U.S. Cl.
CPC ...
G01R 33/56563 (2013.01); G01R 33/4818 (2013.01); G01R 33/5608 (2013.01); G06N 3/08 (2013.01);
Abstract

Disclosed herein is a medical system comprising a memory () storing machine executable instructions () and a trained neural network (). The trained neural network is configured to output corrected magnetic resonance image data () in response to receiving as input a set of magnetic resonance images () each having a different spatially constant frequency off-resonance factor. The medical system further comprises a computational system () configured for controlling the medical system, wherein execution of the machine executable instructions causes the computational system to: receive () k-space data () acquired according to a magnetic resonance imaging protocol: reconstruct () a set of magnetic resonance images () according to the magnetic resonance imaging protocol, wherein each of the set of magnetic resonance images is reconstructed assuming a different spatially constant frequency off-resonance factor chosen from a list of frequency off-resonance factors (); and receive () the corrected magnetic resonance image data in response to inputting the set of magnetic resonance images into the trained neural network.


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