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 12488288 B1

Date of Patent:

Dec. 02, 2025

Filed:

Jan. 17, 2025

Presurgical planning

Applicants:

Gabriel Fine, Salt Lake City, UT (US);

Nathan Silberman, Brooklyn, NY (US);

Inventors:

Gabriel Fine, Salt Lake City, UT (US);

Nathan Silberman, Brooklyn, NY (US);

Assignee:

Other;

Attorney:

Barnes & Thornburg LLP

Primary Examiner:

Fayyaz Alam

Int. Cl.

CPC ...

G06T 7/70 (2017.01); A61B 34/10 (2016.01); A61B 34/20 (2016.01); G06F 18/2413 (2023.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06T 7/00 (2017.01); G06T 7/73 (2017.01); G06V 10/82 (2022.01); G06V 30/19 (2022.01); G06V 30/194 (2022.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 40/63 (2018.01); G16H 50/50 (2018.01); A61B 90/00 (2016.01); A61F 2/01 (2006.01);

U.S. Cl.

CPC ...

G06N 20/00 (2019.01); A61B 34/10 (2016.02); A61B 34/20 (2016.02); G06F 18/2414 (2023.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06T 7/0016 (2013.01); G06T 7/70 (2017.01); G06T 7/75 (2017.01); G06V 10/82 (2022.01); G06V 30/19173 (2022.01); G06V 30/194 (2022.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 40/63 (2018.01); G16H 50/50 (2018.01); A61B 2034/102 (2016.02); A61B 2034/2051 (2016.02); A61B 2034/2065 (2016.02); A61B 2090/367 (2016.02); A61B 2090/376 (2016.02); A61F 2/01 (2013.01); A61F 2/0105 (2020.05); G06T 2207/10072 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/10121 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30021 (2013.01);

Abstract

A system, method, and computer program product for presurgical planning related to an object associated with a medical procedure for a patient is disclosed. A model can be trained for an object as part of a medical procedure, the trained model being generated from one or more machine learning algorithms that are trained on annotated images of the object with spatial information of the object. An imaging computer system can receive or simulate one or more images of the object captured by an imaging device positioned external to the patient. The imaging computer system can further determine, based on applying the trained model to the one or more images of the object, spatial information of the object during the medical procedure. A display can output the one or more images and the spatial information of the object.

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