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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.:

US 11901047 B1

PDFFull Text
Date of Patent:
Feb. 13, 2024

Filed:

Oct. 28, 2020

Medical visual question answering

Applicant:

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

Inventors:

Yuan Zhou, Beijing, CN;

Jing Mei, Beijing, CN;

Shiwan Zhao, Beijing, CN;

Yi Qin Yu, Beijing, CN;

Xu Min, Beijing, CN;

Yan Fei Wang, Shanghai, CN;

Assignee:

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

Attorneys:

CANTOR COLBURN LLP

Michael A. Petrocelli

Primary Examiner:

Edward Park

Int. Cl.
CPC ...
G06T 11/00 (2006.01); G16H 10/20 (2018.01); G16H 30/40 (2018.01); G16H 50/70 (2018.01); G16H 50/20 (2018.01); G06F 16/538 (2019.01); G06N 3/04 (2023.01); G06F 40/30 (2020.01); G06F 40/205 (2020.01); G06F 40/284 (2020.01); A61B 6/00 (2006.01); G16H 30/20 (2018.01); G06V 10/40 (2022.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); A61B 6/03 (2006.01); A61B 5/00 (2006.01);
U.S. Cl.
CPC ...
G16H 10/20 (2018.01); A61B 6/5217 (2013.01); G06F 16/538 (2019.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06F 40/205 (2020.01); G06F 40/284 (2020.01); G06F 40/30 (2020.01); G06N 3/04 (2013.01); G06T 11/00 (2013.01); G06V 10/40 (2022.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); A61B 5/0077 (2013.01); A61B 6/032 (2013.01); G06T 2210/12 (2013.01); G06V 2201/03 (2022.01);
Abstract

Aspects of the invention include a computer-implemented method including extracting a domain-specific object feature from a first image data, wherein the feature describes an object in the first image data. A domain-specific semantic meaning of text data is determined. The object feature is mapped to a portion of the text data, wherein the portion of the text data describes the object. A joint representation of the object and the portion of the text data is created. A second image data and a query directed towards an object in the second image data is received. An answer to the query is generated based on the joint representation.

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