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. 05, 2023

Filed:

May. 07, 2019
Applicant:

Koninklijke Philips N.v., Eindhoven, NL;

Inventors:

Christine Menking Swisher, San Diego, CA (US);

Sheikh Sadid Al Hasan, Cambridge, MA (US);

Jonathan Rubin, Cambridge, MA (US);

Cristhian Mauricio Potes Blandon, Salem, NH (US);

Yuan Ling, Somerville, MA (US);

Oladimeji Feyisetan Farri, Yorktown Heights, NY (US);

Rithesh Sreenivasan, Bangalore, IN;

Assignee:

KONINKLIJKE PHILIPS N.V., Eindhoven, NL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06V 20/64 (2022.01); G06T 7/11 (2017.01); G16H 50/20 (2018.01); G16H 30/40 (2018.01); G06F 40/10 (2020.01); G06N 3/08 (2023.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06V 10/82 (2022.01); G06V 10/44 (2022.01);
U.S. Cl.
CPC ...
G06V 20/64 (2022.01); G06F 40/10 (2020.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06V 10/454 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01);
Abstract

A method () for generating a textual description of a medical image, comprising: receiving () a medical image of an anatomical region, the image comprising one or more abnormalities; segmenting () the anatomical region in the received medical image from a remainder of the image; identifying () at least one of the one or more abnormalities in the segmented anatomical region; extracting () one or more features from the identified abnormality; generating (), using the extracted features and a trained text generation model, a textual description of the identified abnormality; and reporting (), via a user interface of the system, the generated textual description of the identified abnormality.


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