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:
Jul. 09, 2024

Filed:

Dec. 13, 2021
Applicant:

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

Inventors:

Shai Farkash, Hod HaSharon, IL;

Yossef Atiya, Modin-Maccabim-Reut, IL;

Maayan Moshe, Ramat HaSharon, IL;

Moti Ben-Dov, Tel Mond, IL;

Raphael Levy, Jerusalem, IL;

Doron Malka, Tel Aviv, IL;

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); A61B 1/04 (2006.01); A61B 1/06 (2006.01); A61B 1/24 (2006.01); A61C 9/00 (2006.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 70/60 (2018.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G16H 30/40 (2018.01); A61B 1/043 (2013.01); A61B 1/0638 (2013.01); A61B 1/24 (2013.01); A61C 9/0053 (2013.01); G06T 7/0016 (2013.01); G16H 50/20 (2018.01); G16H 70/60 (2018.01); G06N 20/00 (2019.01); G06T 2200/04 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/10064 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30036 (2013.01); G06T 2207/30096 (2013.01);
Abstract

Methods and apparatuses for assessing oral health and automatically providing diagnosis of one or more oral diseases. Described herein are intraoral scanning methods and apparatuses for collecting and analyzing image data and to detect and visualize features within image data that are indicative of oral diseases or conditions, such as gingival inflammation or oral cancer. These methods and apparatuses may be used for identifying and evaluating lesions, redness and inflammation in soft tissue and caries and cracks in the teeth. The methods can include training a machine learning model and using the trained machine learning model to provide a diagnosis of an oral disease or condition based on image data collected using multiple scanning modes of an intraoral scanner.


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