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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 11589955 B1

PDFFull Text
Date of Patent:
Feb. 28, 2023

Filed:

Sep. 26, 2019

Aligner damage prediction using machine learning

Applicant:

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

Inventors:

Viktoria Medvinskaya, Puschino, RU;

Arno Kukk, Moscow, RU;

Andrey Cherkas, Krasnoznamensk, RU;

Anna Akopova, Moscow, RU;

Yuxiang Wang, Newark, CA (US);

Rohit Tanugula, San Jose, CA (US);

Reza Shirazi Aghjari, San Jose, CA (US);

Andrew Jang, San Mateo, CA (US);

Chunhua Li, Cupertino, CA (US);

Jun Sato, San Jose, CA (US);

Luyao Cai, San Jose, CA (US);

Assignee:

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

Attorney:

Lowenstein Sandler LLP

Primary Examiner:

Sean Shechtman

Int. Cl.
CPC ...
A61C 7/00 (2006.01); G06F 17/18 (2006.01); G06N 20/00 (2019.01); A61C 7/08 (2006.01); G06F 30/23 (2020.01); G16H 50/50 (2018.01); G01N 33/44 (2006.01); B33Y 80/00 (2015.01); A61C 9/00 (2006.01); A61C 13/34 (2006.01); B29C 33/38 (2006.01); B29C 51/30 (2006.01); G06F 30/27 (2020.01); B29C 73/00 (2006.01); G06F 30/20 (2020.01); G06F 119/18 (2020.01); G06F 113/22 (2020.01); G06F 111/10 (2020.01); B33Y 50/00 (2015.01); B29L 31/00 (2006.01);
U.S. Cl.
CPC ...
A61C 7/002 (2013.01); A61C 7/08 (2013.01); A61C 9/004 (2013.01); A61C 13/34 (2013.01); B29C 33/3835 (2013.01); B29C 51/30 (2013.01); B29C 73/00 (2013.01); B33Y 80/00 (2014.12); G01N 33/442 (2013.01); G06F 17/18 (2013.01); G06F 30/20 (2020.01); G06F 30/23 (2020.01); G06F 30/27 (2020.01); G06N 20/00 (2019.01); G16H 50/50 (2018.01); B29L 2031/753 (2013.01); B33Y 50/00 (2014.12); G06F 2111/10 (2020.01); G06F 2113/22 (2020.01); G06F 2119/18 (2020.01);
Abstract

Embodiments relate to an aligner breakage solution that tests damage to an aligner using machine learning. A method includes processing data from a digital design for an orthodontic aligner by a trained machine learning model and outputting, by the trained machine learning model, a probability that the orthodontic aligner associated with the digital design will be damaged during manufacturing of the orthodontic aligner. The method further includes making a comparison of the probability that the orthodontic aligner associated with the digital design will be damaged during manufacturing of the orthodontic aligner to a probability threshold and determining whether the orthodontic aligner is a high risk orthodontic aligner based on a result of the comparison. Responsive to determining that the orthodontic aligner is a high risk orthodontic aligner, the method includes performing at least one of a) a corrective action or b) selecting a manufacturing flow for high risk orthodontic aligners.

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