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:
Jan. 20, 2026

Filed:

Jul. 27, 2023
Applicant:

Align Technology, Inc., San Jose, CA (US);

Inventors:

Ofer Saphier, Rehovot, IL;

Avi Kopelman, Palo Alto, CA (US);

Moti Ben Dov, Tel Mond, IL;

Ran Katz, Hod Hasharon, IL;

Shai Farkash, Hod Hasharon, IL;

Roy Fahn, Petach Tikva, IL;

Michael Chang, Zurich, CH;

Niko Benjamin Huber, Zug, CH;

Eric P. Meyer, Zurich, CH;

Gustavo Ismael, Mainz, DE;

Zelko Relic, Pleasanton, CA (US);

Maik Gerth, Hessen, DE;

Assignee:

Align Technology, Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61C 9/00 (2006.01);
U.S. Cl.
CPC ...
A61C 9/0053 (2013.01);
Abstract

A method may include obtaining a first 3D model of an upper jaw of a patient using an intraoral scanner and obtaining a second 3D model of the lower jaw of the patient using the intraoral scanner. The method may also include capturing a series of 2D images of the upper and lower jaws of the patient as the patient is moves the upper jaw and lower jaw in dynamic occlusion and processing the captured series of 2D images to identify features associated with the upper jaw of the patient and the lower jaw of the patient. For each 2D image in the captured series of 2D images, the method may include identifying a relative position of the first 3D model and the second 3D model based on alignment of features in the first 3D model and second 3D model with the features identified in the 2D image to generate a series of relative positions of the first 3D model and the second 3D model. The method may also include modeling dynamic occlusion of the upper jaw and the lower jaw of the patient based on the series of relative positions of the first 3D model and the second 3D model.


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