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:
Aug. 15, 2023

Filed:

Dec. 23, 2020
Applicant:

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

Inventors:

Guotu Li, Durham, NC (US);

Christopher E. Cramer, Durham, NC (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 15/00 (2011.01); A61C 7/00 (2006.01); G06T 19/20 (2011.01); G06T 7/13 (2017.01); G06T 7/11 (2017.01); G06T 7/00 (2017.01); G16H 50/50 (2018.01); G16H 30/40 (2018.01); G16H 20/40 (2018.01); G06N 3/04 (2023.01); G06N 3/084 (2023.01); G06T 17/20 (2006.01);
U.S. Cl.
CPC ...
A61C 7/002 (2013.01); G06N 3/04 (2013.01); G06N 3/084 (2013.01); G06T 7/11 (2017.01); G06T 7/13 (2017.01); G06T 7/97 (2017.01); G06T 17/20 (2013.01); G06T 19/20 (2013.01); G16H 20/40 (2018.01); G16H 30/40 (2018.01); G16H 50/50 (2018.01); A61C 2007/004 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30036 (2013.01); G06T 2210/41 (2013.01); G06T 2210/56 (2013.01);
Abstract

Provided herein are systems and methods for optimizing a 3D model of an individual's teeth. A 3D dental model may be reconstructed from 3D parameters. A differentiable renderer may be used to derive a 2D rendering of the individual's dentition. 2D image(s) of an individual's dentition may be obtained, and features may be extracted from the 2D image(s). Image loss between the 2D rendering and the 2D image(s) can be derived, and back-propagation from the image loss can be used to calculate gradients of the loss to optimize the 3D parameters. A machine learning model can also be trained to predict a 3D dental model from 2D images of an individual's dentition.


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