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:
May. 28, 2024

Filed:

Sep. 03, 2020
Applicant:

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

Inventors:

Assaf Weiss, Yavne, IL;

Maxim Volgin, Moscow, RU;

Pavel Agniashvili, Moscow, RU;

Chad Clayton Brown, Cary, NC (US);

Alexander Raskhodchikov, Moscow, RU;

Avi Kopelman, Palo Alto, CA (US);

Michael Sabina, Campbell, CA (US);

Moti Ben-Dov, Tel Mond, IL;

Shai Farkash, Hod Hasharon, IL;

Igor Makiewsky, Ramat Gan, IL;

Maayan Moshe, Ramat Hasharon, IL;

Ofer Saphier, Rechovot, IL;

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/12 (2017.01); A61C 13/00 (2006.01); A61C 13/34 (2006.01); G06N 3/047 (2023.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G16H 30/40 (2018.01);
U.S. Cl.
CPC ...
G06T 7/12 (2017.01); A61C 13/0004 (2013.01); A61C 13/0019 (2013.01); A61C 13/34 (2013.01); G06N 3/047 (2023.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G16H 30/40 (2018.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30036 (2013.01);
Abstract

Methods and systems are described that mark and/or correct margin lines and/or other features of dental sites. In one example a three-dimensional model of a dental site is generated from intraoral scan data of the dental site, the three-dimensional model comprising a representation of a preparation tooth. An image of the preparation tooth is received or generated. Data from the image is processed using a trained machine learning model that has been trained to identify margin lines of preparation teeth, wherein the trained machine learning model outputs a probability map comprising, for each pixel in the image, a probability that the pixel depicts a margin line. The three-dimensional model of the dental site is then updated by marking the margin line on the representation of the preparation tooth based on the probability map.


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