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:
Mar. 25, 2025

Filed:

Dec. 14, 2021
Applicant:

Stryker Corporation, Kalamazoo, MI (US);

Inventors:

Brian Fouts, Morgan Hill, CA (US);

Jakob Kemper, Heemstede, NL;

Heiko Michael Gottschling, Munich, DE;

Manuel Schroeder, Ellingen, DE;

Assignee:

Stryker Corporation, Portage, MI (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 34/10 (2016.01); A61B 90/00 (2016.01); G06T 7/00 (2017.01); G06T 7/32 (2017.01);
U.S. Cl.
CPC ...
A61B 34/10 (2016.02); A61B 90/37 (2016.02); G06T 7/0012 (2013.01); G06T 7/32 (2017.01); A61B 2034/105 (2016.02); A61B 2090/374 (2016.02); A61B 2090/3764 (2016.02); G06T 2207/10028 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10121 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30008 (2013.01);
Abstract

A method for modeling a joint before, during, and/or after a medical procedure includes receiving first imaging data capturing the joint from a first imaging perspective and second imaging data capturing the joint from a second imaging perspective that is different than the first imaging perspective, the first and second imaging data generated intraoperatively via a two-dimensional imaging modality, generating three-dimensional image data by back-projecting the first and second imaging data in three-dimensional space in accordance with a relative difference between the first and second imaging perspectives, generating a three-dimensional model of the joint based on processing the three-dimensional image data with a machine learning model trained on imaging data generated via at least a three-dimensional imaging modality, and displaying a visualization based on the three-dimensional model of the joint during the medical procedure.


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