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. 01, 2020

Filed:

Jun. 07, 2018
Applicant:

Siemens Healthcare Gmbh, Erlangen, DE;

Inventors:

Xiao Chen, Princeton, NJ (US);

Boris Mailhe, Plainsboro, NJ (US);

Benjamin L. Odry, West New York, NJ (US);

Pascal Ceccaldi, Princeton, NJ (US);

Mariappan S. Nadar, Plainsboro, NJ (US);

Assignee:

Siemens Healthcare GmbH, Erlangen, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01R 33/56 (2006.01); G06T 5/00 (2006.01); G01R 33/565 (2006.01); G06T 11/00 (2006.01); G01R 33/48 (2006.01);
U.S. Cl.
CPC ...
G01R 33/5608 (2013.01); G01R 33/4818 (2013.01); G01R 33/56509 (2013.01); G06T 11/008 (2013.01); G06T 2210/41 (2013.01);
Abstract

For artifact reduction in a magnetic resonance imaging system, deep learning trains an image-to-image neural network to generate an image with reduced artifact from input, artifacted MR data. For application, the image-to-image network may be applied in real time with a lower computational burden than typical post-processing methods. To handle a range of different imaging situations, the image-to-image network may (a) use an auxiliary map as an input with the MR data from the patient, (b) use sequence metadata as a controller of the encoder of the image-to-image network, and/or (c) be trained to generate contrast invariant features in the encoder using a discriminator that receives encoder features.


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