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:
Feb. 25, 2025

Filed:

Feb. 14, 2022
Applicant:

Fujifilm Sonosite, Inc., Bothell, WA (US);

Inventors:

Davin Dhatt, Woodinville, WA (US);

Thomas Duffy, Snohomish, WA (US);

Adam Pely, Seattle, WA (US);

Christopher White, North Vancouver, CA;

Andrew Lundberg, Woodinville, WA (US);

Paul Danset, Kirkland, WA (US);

Craig Chamberlain, Seattle, WA (US);

Diku Mandavia, Los Angeles, CA (US);

Assignee:

FUJIFILM SONOSITE, INC., Bothell, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06N 5/04 (2023.01); G16H 30/20 (2018.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06N 5/04 (2013.01); G16H 30/20 (2018.01); G06T 2207/10132 (2013.01);
Abstract

Examples herein include methods, systems, and computer program products for utilizing neural networks in ultrasound systems. The methods include processor(s) of a computing device identifying a neural network for implementation on the computing device to generate, based on ultrasound data, inferences and confidence levels for the inferences, the computing device being communicatively coupled via a computing network to an ultrasound machine configured to generate the ultrasound data. The processor(s) implements the neural network on the computing device, including configuring the neural network to generate an inference and a confidence level for at least one image of the images. The processor(s) obtains the ultrasound data including images from the ultrasound machine. The processor(s) determines, for the at least one image, an accuracy of the inference and the confidence level. The processor(s) automatically reconfigures the neural network to increase the accuracy based on the determining the accuracy.


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