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. 31, 2022

Filed:

May. 15, 2020
Applicant:

Retrace Labs, San Francisco, CA (US);

Inventors:

Vasant Kearney, San Francisco, CA (US);

Ali Sadat, San Francisco, CA (US);

Stephen Chan, San Francisco, CA (US);

Hamid Hakmatian, San Francisco, CA (US);

Yash Patel, San Francisco, CA (US);

Assignee:

Retrace Labs, San Francisco, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06T 7/00 (2017.01); G06T 7/70 (2017.01); G16H 30/40 (2018.01); A61C 19/04 (2006.01); G06K 9/62 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61C 19/043 (2013.01); G06K 9/6256 (2013.01); G06T 7/70 (2017.01); G16H 30/40 (2018.01); G06T 2207/20076 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30036 (2013.01);
Abstract

Dental images are processed according to a first machine learning model to determine teeth labels. The teeth labels and image are concatenated and processed using a second machine learning model to label anatomy including CEJ, JE, GM, and Bone. The anatomy labels, teeth labels, and image are concatenated and processed using a third machine learning model to obtain feature measurements, such as pocket depth and clinical attachment level. The feature measurements, anatomy labels, teeth labels, and image may be concatenated and input to a fourth machine learning model to obtain a diagnosis for a periodontal condition. Feature measurements and/or the diagnosis may be processed according to a diagnosis hierarchy to determine whether a treatment is appropriate. Machine learning models may further be used to reorient, decontaminate, and restore the image prior to processing. Machine learning models may be embodied as CNN, GAN, and cyclic GAN.


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