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:
Nov. 16, 2021

Filed:

Oct. 17, 2016
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Colin Compas, San Jose, CA (US);

Yaniv Gur, San Jose, CA (US);

Mehdi Moradi, San Jose, CA (US);

Mohammadreza Negahdar, San Jose, CA (US);

Tanveer Syeda-Mahmood, San Jose, CA (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16H 10/60 (2018.01); G06Q 10/06 (2012.01); G16H 50/20 (2018.01); G06K 9/62 (2006.01); G06K 9/00 (2006.01); G16H 30/20 (2018.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06K 9/32 (2006.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06N 5/00 (2006.01);
U.S. Cl.
CPC ...
G16H 10/60 (2018.01); G06K 9/00 (2013.01); G06K 9/0053 (2013.01); G06K 9/6274 (2013.01); G06Q 10/0633 (2013.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01); G06K 9/3266 (2013.01); G06K 2209/01 (2013.01); G06K 2209/05 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 5/003 (2013.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01);
Abstract

Workflows for automatic measurement of Doppler is provided. In various embodiments, a plurality of frames of a medical video are read. A mode label indicative of a mode of each of the plurality of frames is determined. At least one of the plurality of frames is provided to a trained feature generator. The at least one of the plurality of frames have the same mode label. At least one feature vector is obtained from the trained feature generator corresponding to the at least one of the plurality of frames. At least one feature vector is provided to a trained classifier. A valve label indicative of a valve is obtained from the trained classifier corresponding to the at least one of the plurality of frames. One or more measurement is extracted indicative of a disease condition from those of the at least one of the plurality of frames matching a predetermined valve label.


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