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:
Jul. 28, 2026

Filed:

May. 21, 2024
Applicant:

GE Precision Healthcare Llc, Waukesha, WI (US);

Inventors:

Doron Shaked, Tivon, IL;

Amitay Lev, Or Akiva, IL;

Uriel Cohen, Haifa, IL;

Hannah Michele Ornstein, Haifa, IL;

Elay Dahan, Haifa, IL;

Chandan Kumar Mallappa Aladahalli, Bengaluru, IN;

Gopal Biligeri Avinash, Concord, CA (US);

Assignee:

GE PRECISION HEALTHCARE LLC, Waukesha, WI (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 30/20 (2018.01); G06T 11/60 (2006.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); H04N 1/387 (2006.01);
U.S. Cl.
CPC ...
G16H 30/20 (2018.01); G06T 11/60 (2013.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G06V 2201/07 (2022.01); H04N 1/387 (2013.01);
Abstract

Systems or techniques that facilitate medical image privacy preservation via image synthesis and filtration are provided. In various embodiments, a system can access a medical image for which a first artificial neural network has produced an inferencing task result. In various aspects, the system can train a second artificial neural network on the medical image to perform image synthesis. In various instances, the system can generate, via execution of the second artificial neural network post-training, a set of synthetic variants of the medical image. In various cases, the system can fine-tune the first artificial neural network using at least some of the set of synthetic variants of the medical image rather than using the medical image.


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