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:
Apr. 27, 2021

Filed:

Dec. 10, 2018
Applicant:

Siemens Healthcare Gmbh, Erlangen, DE;

Inventors:

Sandro Braun, Karlsruhe, DE;

Boris Mailhe, Plainsboro, NJ (US);

Xiao Chen, Princeton, NJ (US);

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

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

Assignee:

Siemens Healthcare GmbH, Erlangen, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G01R 33/54 (2006.01); G01R 33/56 (2006.01); G06K 9/03 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G01R 33/543 (2013.01); G01R 33/5608 (2013.01); G06K 9/036 (2013.01); G06K 9/6215 (2013.01); G06K 9/6257 (2013.01); G06K 9/6259 (2013.01); G06K 9/6269 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30168 (2013.01);
Abstract

For classifying magnetic resonance image quality or training to classify magnetic resonance image quality, deep learning is used to learn features distinguishing between corrupt images base on simulation and measured similarity. The deep learning uses synthetic data without quality annotation, allowing a large set of training data. The deep-learned features are then used as input features for training a classifier using training data annotated with ground truth quality. A smaller training data set may be needed to train the classifier due to the use of features learned without the quality annotation.


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