公开(公告)号：US20230157790A1

公开(公告)日：2023-05-25

申请号：US18159598

申请日：2023-01-25

Applicant: Align Technology, Inc.

Inventor： Viktoria Medvinskaya ,  Arno Kukk ,  Andrey Cherkas ,  Anna Akopova ,  Yuxiang Wang ,  Rohit Tanugula ,  Reza Shirazi Aghjari ,  Andrew Jang ,  Chunhua Li ,  Jun Sato ,  Luyao Cai

IPC: A61C7/00 ,  G06F17/18 ,  G06N20/00 ,  A61C7/08 ,  G06F30/23 ,  G16H50/50 ,  G01N33/44 ,  B33Y80/00 ,  A61C9/00 ,  A61C13/34 ,  B29C33/38 ,  B29C51/30 ,  G06F30/27 ,  B29C73/00 ,  G06F30/20

CPC classification number: A61C7/002 ,  G06F17/18 ,  G06N20/00 ,  A61C7/08 ,  G06F30/23 ,  G16H50/50 ,  G01N33/442 ,  B33Y80/00 ,  A61C9/004 ,  A61C13/34 ,  B29C33/3835 ,  B29C51/30 ,  G06F30/27 ,  B29C73/00 ,  G06F30/20 ,  G06F2119/18

Abstract: Embodiments relate to an aligner breakage solution that tests damage to an aligner using machine learning. A method includes of training a machine learning model to predict damage to an orthodontic aligner includes gathering a training dataset comprising digital designs for a plurality of orthodontic aligners, wherein each digital design is associated with a respective orthodontic aligner of the plurality of orthodontic aligners, and wherein each digital design comprises metadata indicating whether the associated respective orthodontic aligner was damaged during manufacturing of the associated respective orthodontic aligner. The method further includes training the machine learning model using the training dataset, wherein the machine learning model is trained to process data from a digital design for an orthodontic aligner and to output a probability that the orthodontic aligner associated with the digital design will be damaged during manufacturing of the orthodontic aligner.

公开(公告)号：US11278375B2

公开(公告)日：2022-03-22

申请号：US16584786

申请日：2019-09-26

Applicant: Align Technology, Inc.

Inventor： Yuxiang Wang ,  Rohit Tanugula ,  Reza Shirazi Aghjari ,  Andrew Jang ,  Chunhua Li ,  Jun Sato ,  Luyao Cai ,  Viktoria Medvinskaya ,  Arno Kukk ,  Andrey Cherkas ,  Anna Akopova ,  Kangning Su

IPC: G06T15/00 ,  A61C7/00 ,  G06F17/18 ,  G06N20/00 ,  A61C7/08 ,  G06F30/23 ,  G16H50/50 ,  G01N33/44 ,  B33Y80/00 ,  A61C9/00 ,  A61C13/34 ,  B29C33/38 ,  B29C51/30 ,  G06F119/18 ,  G06F113/22 ,  G06F111/10 ,  B33Y50/00 ,  B29L31/00

Abstract: Embodiments relate to an aligner breakage solution. A method includes obtaining a digital design of a polymeric aligner for a dental arch of a patient. The polymeric aligner is shaped to apply forces to teeth of the dental arch. The method also includes performing an analysis on the digital design of the polymeric aligner using at least one of a) a trained machine learning model, b) a numerical simulation, c) a geometry evaluator or d) a rules engine. The method may also include determining, based on the analysis, whether the digital design of the polymeric aligner includes probable points of damage, wherein for a probable point of damage there is a threshold probability that breakage, deformation, or warpage will occur. The method may also include, responsive to determining that the digital design of the polymeric aligner comprises probable points of damage, performing corrective actions based on the probable points of damage.

公开(公告)号：US11589955B2

公开(公告)日：2023-02-28

申请号：US16584794

申请日：2019-09-26

Applicant: Align Technology, Inc.

Inventor： Viktoria Medvinskaya ,  Arno Kukk ,  Andrey Cherkas ,  Anna Akopova ,  Yuxiang Wang ,  Rohit Tanugula ,  Reza Shirazi Aghjari ,  Andrew Jang ,  Chunhua Li ,  Jun Sato ,  Luyao Cai

IPC: A61C7/00 ,  G06F17/18 ,  G06N20/00 ,  A61C7/08 ,  G06F30/23 ,  G16H50/50 ,  G01N33/44 ,  B33Y80/00 ,  A61C9/00 ,  A61C13/34 ,  B29C33/38 ,  B29C51/30 ,  G06F30/27 ,  B29C73/00 ,  G06F30/20 ,  G06F119/18 ,  G06F113/22 ,  G06F111/10 ,  B33Y50/00 ,  B29L31/00

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.