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.
Patent No.:
Date of Patent:
Aug. 11, 2020
Filed:
Oct. 27, 2017
Applicant:
General Electric Company, Schenectady, NY (US);
Inventors:
Alberto Santamaria-Pang, Schnectady, NY (US);
Daniel Eugene Meyer, Rexford, NY (US);
Michael Ernest Marino, Niskayuna, NY (US);
Qing Li, Niskayuna, NY (US);
Dmitry V. Dylov, Niskayuna, NY (US);
Aritra Chowdhury, Troy, NY (US);
Assignee:
GENERAL ELECTRIC COMPANY, Schenectady, NY (US);
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G09B 23/30 (2006.01); G06T 7/00 (2017.01); G16H 50/20 (2018.01); G06K 9/44 (2006.01); G06T 7/11 (2017.01); G06T 7/155 (2017.01); G16H 50/50 (2018.01);
U.S. Cl.
CPC ...
G06K 9/6256 (2013.01); G06K 9/44 (2013.01); G06K 9/6267 (2013.01); G06K 9/6274 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 7/155 (2017.01); G09B 23/30 (2013.01); G09B 23/303 (2013.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G06K 2209/05 (2013.01); G06N 3/0454 (2013.01); G06N 3/084 (2013.01); G06T 2200/04 (2013.01); G06T 2207/10056 (2013.01); G06T 2207/10064 (2013.01); G06T 2207/30016 (2013.01); G06T 2207/30101 (2013.01); G06T 2207/30172 (2013.01);
Abstract
The present approach relates to the use of trained artificial neural networks, such as convolutional neural networks, to classify vascular structures, such as using a hierarchical classification scheme. In certain approaches, the artificial neural network is trained using training data that is all or partly derived from synthetic vascular representations.