IP Library Granted Patent US 12,453,473
Granted Patent B2
US 12,453,473 · App. 17/230,825 · Granted Oct 28, 2025

Smart scanning for intraoral scanners

Inventors: Ofer Saphier (Rechovot, IL); Pavel Agniashvili (Moscow, RU); Moti Ben-Dov (Tel Mond, IL); Ran Katz (Hod Hasharon, IL); Avi Kopelman (Palo Alto, CA); Maxim Volgin (Moscow, RU); Doron Malka (Tel Aviv, IL); Avraham Zulti (Modiin, IL); Pavel Veryovkin (Krasnogorsk, RU); Maayan Moshe (Ramat Hasharon, IL); Ido Tishel (Kfar Bilu, IL); Adi Levin (Nes Tziona, IL); Shai Farkash (Hod Hasharon, IL); Inna Karapetyan (Modiin, IL); Dina Bova (Shaar Efraim, IL); Edi Fridman (Rishon le Zion, IL); Jonathan Coslovsky (Rehovot, IL)
Assignee: Align Technology, Inc.
A61B5/004A61B5/0033A61B5/0088A61B5/7267A61B5/7475G06T17/20G06V10/764G06V10/82G06V20/64G06T2210/41
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,453,473
App. No.
17/230,825
Granted
Oct 28, 2025
Kind
B2
Abstract

A method of intraoral scanning includes receiving a first one or more intraoral scans of a patient's oral cavity; automatically determining, based on processing of the first one or more intraoral scans, a first scanning role associated with the first one or more intraoral scans, wherein the first scanning role is a first one of an upper dental arch role, a lower dental arch role or a bite role; and determining a first three-dimensional surface associated with the first scanning role.

Claims (86)

1. A computer readable medium comprising instructions that, when executed by a processing device, cause the processing device to perform operations comprising:

receiving a first one or more intraoral scans of a patient's oral cavity;

determining that the first one or more intraoral scans depict a first dental arch of a patient;

determining a first three-dimensional surface of the first dental arch using the first one or more intraoral scans; and

determining that the first dental arch of the patient is a lower dental arch rather than an upper dental arch responsive to determining that at least one of the first three-dimensional surface or some of the first one or more intraoral scans include a representation of a tongue, wherein for at least one of the first three-dimensional surface or an intraoral scan of the first one or more intraoral scans the lower dental arch is detected if at least a threshold number of points in the first three-dimensional surface or the intraoral scan depict the tongue.

2. The computer readable medium of claim 1 , the operations further comprising:

determining that the first three-dimensional surface of the first dental arch is complete; and

automatically generating a first three-dimensional model of the first dental arch responsive to determining that the first dental arch is complete.

3. The computer readable medium of claim 1 , wherein the first one or more intraoral scans of the patient's oral cavity are received without first receiving an indication of whether the first dental arch is the upper dental arch or the lower dental arch, or receiving an indication that a new dental arch is being scanned.

4. The computer readable medium of claim 1 , wherein determining that the first one or more intraoral scans depict the first dental arch of the patient and determining that the first dental arch of the patient is the lower dental arch comprises:

inputting the first one or more intraoral scans into a machine learning model that has been trained to classify intraoral scans as depicting the upper dental arch, the lower dental arch, or a bite, wherein the machine learning model outputs a first classification indicating whether the first dental arch of the patient is the upper dental arch or the lower dental arch.

5. The computer readable medium of claim 4 , wherein the first one or more intraoral scans comprises a plurality of intraoral scans, and wherein determining that the first one or more intraoral scans depict the first dental arch of the patient and determining that the first dental arch of the patient is the lower dental arch comprises:

inputting each intraoral scan of the plurality of intraoral scans into the machine learning model, wherein the machine learning model outputs a plurality of classifications, each of the plurality of classifications being associated with one of the plurality of intraoral scans; and

determining that a majority of the classifications output by the machine learning model indicate that the first dental arch is the lower dental arch.

6. The computer readable medium of claim 5 , wherein the first one or more intraoral scans comprises a plurality of intraoral scans, and wherein determining that the first one or more intraoral scans depict the first dental arch of the patient and determining that the first dental arch of the patient is the lower dental arch comprises:

inputting each intraoral scan of the plurality of intraoral scans into the machine learning model, wherein the machine learning model outputs a plurality of classifications, each of the plurality of classifications being associated with one of the plurality of intraoral scans; and

determining a moving average of the plurality of classifications output by the machine learning model, wherein the moving average indicates whether the first dental arch is the upper dental arch or the lower dental arch.

7. The computer readable medium of claim 5 , wherein the first one or more intraoral scans comprise a plurality of intraoral scans received in sequential order, wherein the first one or more intraoral scans are input into the machine learning model in the sequential order, and wherein the machine learning model is a recurrent neural network.

8. The computer readable medium of claim 5 , wherein for each of the first one or more intraoral scans the machine learning model outputs a confidence value, the operations further comprising:

for each of the first one or more intraoral scans, determining whether the confidence value associated with an output of the machine learning model for that intraoral scan is below a confidence threshold; and

discarding those outputs of the machine learning model having confidence values below the confidence threshold.

9. The computer readable medium of claim 5 , wherein the first one or more intraoral scans are input into the machine learning model as the first one or more intraoral scans are received and before intraoral scanning of the first dental arch is complete, the operations further comprising:

generating a height map of the first dental arch by projecting at least a portion of the first three-dimensional surface of the first dental arch onto a plane; and

processing data from the height map using the machine learning model or an alternate machine learning model that has been trained to classify height maps as depicting the upper dental arch, the lower dental arch, or a bite, wherein the machine learning model or the alternate machine learning model outputs a second classification indicating whether the first dental arch is the upper dental arch or the lower dental arch with a higher level of accuracy as compared to the first classification.

10. The computer readable medium of claim 1 , the operations further comprising:

labeling the first one or more intraoral scans as belonging to a first segment of the first dental arch;

receiving a second one or more intraoral scans of the patient's oral cavity;

determining that the second one or more intraoral scans depict the first dental arch of the patient; and

labeling the second one or more intraoral scans as belonging to a second segment of the first dental arch.

11. The computer readable medium of claim 1 , the operations further comprising:

determining whether the first one or more intraoral scans depict a lingual view, a buccal view or an occlusal view of the first dental arch.

12. A computer readable medium comprising instructions that, when executed by a processing device, cause the processing device to perform operations comprising:

receiving a first one or more intraoral scans of a patient's oral cavity;

determining that the first one or more intraoral scans depict a first dental arch of a patient;

determining that the first dental arch is an upper dental arch;

determining a first three-dimensional surface of the first dental arch using the first one or more intraoral scans;

receiving a user input indicating that the first one or more intraoral scans depict a lower dental arch of the patient;

determining that the user input is incorrect; and

outputting a notification that the first one or more intraoral scans depict the upper dental arch of the patient.

13. A computer readable medium comprising instructions that, when executed by a processing device, cause the processing device to perform operations comprising:

receiving a first one or more intraoral scans of a patient's oral cavity;

determining that the first one or more intraoral scans depict a first dental arch of a patient;

determining whether the first dental arch of the patient is an upper dental arch or a lower dental arch;

receiving a second intraoral scan that depicts a first bite relation between the upper dental arch and the lower dental arch, the second intraoral scan having been generated at a first time;

receiving a third intraoral scan that depicts a second bite relation between the upper dental arch and the lower dental arch, the third intraoral scan having been generated at a second time;

determining a first difference between the first bite relation and the second bite relation;

determining a second difference between the first time and the second time; and

determining, based at least in part on the first difference and the second difference, whether the second intraoral scan and the third intraoral scan depict a same bite of the patient or a different bite of the patient.

14. A computer readable medium comprising instructions that, when executed by a processing device, cause the processing device to perform operations comprising:

receiving a first one or more intraoral scans of a patient's oral cavity;

determining that the first one or more intraoral scans depict a first dental arch of a patient and determining whether the first dental arch of the patient is an upper dental arch or a lower dental arch, wherein determining that the first one or more intraoral scans depict the first dental arch of the patient and determining whether the first dental arch of the patient is the upper dental arch or the lower dental arch comprises:

determining whether at least one of the first one or more intraoral scans was generated before an intraoral scanner was inserted into the patient's oral cavity depicts a nose or a chin; and

determining that the first dental arch of the patient is the lower dental arch responsive to determining that at least one of the first one or more intraoral scans include a representation of a chin; or

determining that the first dental arch of the patient is the upper dental arch responsive to determining that at least one of the first one or more intraoral scans include a representation of a nose; and

determining a first three-dimensional surface of the first dental arch using the first one or more intraoral scans.

15. The computer readable medium of claim 14 , the operations further comprising:

detecting, based on data from an inertial measurement unit of an intraoral scanner that generated the first one or more intraoral scans, that the intraoral scanner was rotated about a longitudinal axis of the intraoral scanner after the first one or more intraoral scans were generated;

receiving a second one or more intraoral scans of the patient's oral cavity after the intraoral scanner was rotated about the longitudinal axis;

determining that the second one or more intraoral scans depict the lower dental arch if the first dental arch is the upper dental arch; and

determining that the second one or more intraoral scans depict the upper dental arch if the first dental arch is the lower dental arch.

16. A system comprising:

an intraoral scanner to generate a first one or more intraoral scans of a patient's oral cavity; and

a computing device connected to the intraoral scanner via a wired or wireless connection, the computing device configured to perform operations comprising:

receiving the first one or more intraoral scans of the patient's oral cavity;

determining that the first one or more intraoral scans depict a first dental arch of the patient and determining whether the first dental arch is an upper dental arch or a lower dental arch by:

generating an image of the first dental arch, the image comprising a height map; and

processing data from the image using a machine learning model that has been trained to classify images of dental arches as depicting the upper dental arch, the lower dental arch, or a bite, wherein the machine learning model outputs a classification indicating whether the first dental arch is the upper dental arch or the lower dental arch; and

determining a first three-dimensional surface of the first dental arch using the first one or more intraoral scans.

17. The system of claim 16 , wherein the first dental arch is determined to be the upper dental arch, and wherein the computing device is further configured to perform operations comprising:

receiving a second one or more intraoral scans of the patient's oral cavity generated by the intraoral scanner;

processing the second one or more intraoral scans;

determining, based on the processing of the second one or more intraoral scans, that the second one or more intraoral scans depict a second dental arch of the patient and that the second dental arch is a lower dental arch; and

automatically generating a second three-dimensional surface of the second dental arch using the second one or more intraoral scans.

18. The system of claim 17 , the computing device configured to perform operations further comprising:

receiving a third one or more intraoral scans of the patient's oral cavity;

processing the third one or more intraoral scans; and

determining, based on the processing of the third one or more intraoral scans, that a patient bite is depicted in the third one or more intraoral scans.

19. The system of claim 17 , wherein the first three-dimensional surface is generated as the first one or more intraoral scans are received, the computing device configured to perform operations further comprising:

automatically determining that a user has transitioned from scanning of the first dental arch to scanning of the second dental arch; and

switching from generation of the first three-dimensional surface to generation of the second three-dimensional surface.

20. The system of claim 16 , wherein the first three-dimensional surface is generated prior to determining whether the first dental arch is the upper dental arch or the lower dental arch, and wherein the image of the first dental arch is generated by projecting at least a portion of the first three-dimensional surface of the first dental arch onto a two-dimensional surface.

21. A computer readable medium comprising instructions that, when executed by a processing device, cause the processing device to perform operations comprising:

receiving a first one or more intraoral scans of a patient's oral cavity;

determining that the first one or more intraoral scans depict a first dental arch of a patient;

determining a first three-dimensional surface of the first dental arch using the first one or more intraoral scans; and

determining the first dental arch of the patient is an upper dental arch responsive to determining that at least one of the first three-dimensional surface or some of the first one or more intraoral scans include a representation of an upper palate, wherein for at least one of the first three-dimensional surface or the intraoral scan of the first one or more intraoral scans the upper dental arch is detected if at least a threshold number of points in the first three-dimensional surface or the intraoral scan depict the upper palate.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 14, 2021
From: COSLOVSKY, JONATHAN
To: ALIGN TECHNOLOGY, INC.
Reel/Frame 055921/0949 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 14, 2021
From: SAPHIER, OFER; AGNIASHVILI, PAVEL; BEN-DOV, MOTI; KATZ, RAN; KOPELMAN, AVI; VOLGIN, MAXIM; MALKA, DORON; ZULTI, AVRAHAM; VERYOVKIN, PAVEL; MOSHE, MAAYAN; TISHEL, IDO; LEVIN, ADI; FARKASH, SHAI; KARAPETYAN, INNA; BOVA, DINA; FRIDMAN, EDI
To: ALIGN TECHNOLOGY, INC.
Reel/Frame 055921/0952 →
Continuity (2)
Provisional Application 63010667 · Apr 15, 2020
Related Publication 20210321872A1 · Oct 21, 2021
References Cited (117)
US 6099314A · Kopelman et al. · 2000 [cited by applicant]
US 6334772B1 · Taub et al. · 2002 [cited by applicant]
US 6334853B1 · Kopelman et al. · 2002 [cited by applicant]
US 6463344B1 · Pavlovskaia et al. · 2002 [cited by applicant]
US 6540512B1 · Sachdeva et al. · 2003 [cited by applicant]
US 6542249B1 · Kofman et al. · 2003 [cited by applicant]
US 6633789B1 · Nikolskiy et al. · 2003 [cited by applicant]
US 6664986B1 · Kopelman et al. · 2003 [cited by applicant]
US 6697164B1 · Babayoff et al. · 2004 [cited by applicant]
US 6845175B2 · Kopelman et al. · 2005 [cited by applicant]
US 6979196B2 · Nikolskiy et al. · 2005 [cited by applicant]
US 7030383B2 · Babayoff et al. · 2006 [cited by applicant]
US 7202466B2 · Babayoff et al. · 2007 [cited by applicant]
US 7255558B2 · Babayoff et al. · 2007 [cited by applicant]
US 7286954B2 · Kopelman et al. · 2007 [cited by applicant]
US 7319529B2 · Babayoff · 2008 [cited by applicant]
US 7373286B2 · Nikolskiy et al. · 2008 [cited by applicant]
US 7507088B2 · Taub et al. · 2009 [cited by applicant]
US 7545372B2 · Kopelman et al. · 2009 [cited by applicant]
US 7698068B2 · Babayoff · 2010 [cited by applicant]
US 7916911B2 · Kaza et al. · 2011 [cited by applicant]
US 8108189B2 · Chelnokov et al. · 2012 [cited by applicant]
US 8244028B2 · Kuo et al. · 2012 [cited by applicant]
US 8587582B2 · Matov et al. · 2013 [cited by applicant]
US 8948482B2 · Levin · 2015 [cited by applicant]
US D742518S · Barak et al. · 2015 [cited by applicant]
US 9192305B2 · Levin · 2015 [cited by applicant]
US 9261356B2 · Lampert et al. · 2016 [cited by applicant]
US 9261358B2 · Atiya et al. · 2016 [cited by applicant]
US 9299192B2 · Kopelman · 2016 [cited by applicant]
US D760901S · Barak et al. · 2016 [cited by applicant]
US 9393087B2 · Moalem · 2016 [cited by applicant]
US 9408679B2 · Kopelman · 2016 [cited by applicant]
US 9431887B2 · Boltanski · 2016 [cited by applicant]
US 9439568B2 · Atiya et al. · 2016 [cited by applicant]
US 9451873B1 · Kopelman et al. · 2016 [cited by applicant]
US D768861S · Barak et al. · 2016 [cited by applicant]
US D771817S · Barak et al. · 2016 [cited by applicant]
US 9491863B2 · Boltanski · 2016 [cited by applicant]
US D774193S · Makmel et al. · 2016 [cited by applicant]
US 9510757B2 · Kopelman et al. · 2016 [cited by applicant]
US 9660418B2 · Atiya et al. · 2017 [cited by applicant]
US 9668829B2 · Kopelman · 2017 [cited by applicant]
US 9675430B2 · Verker et al. · 2017 [cited by applicant]
US 9693839B2 · Atiya et al. · 2017 [cited by applicant]
US 9717402B2 · Lampert et al. · 2017 [cited by applicant]
US 9724177B2 · Levin · 2017 [cited by applicant]
US 9844426B2 · Atiya et al. · 2017 [cited by applicant]
US 10076389B2 · Wu et al. · 2018 [cited by applicant]
US 10098714B2 · Kuo · 2018 [cited by applicant]
US 10108269B2 · Sabina et al. · 2018 [cited by applicant]
US 10111581B2 · Makmel · 2018 [cited by applicant]
US 10111714B2 · Kopelman et al. · 2018 [cited by applicant]
US 10123706B2 · Elbaz et al. · 2018 [cited by applicant]
US 10136972B2 · Sabina et al. · 2018 [cited by applicant]
US 10380212B2 · Elbaz et al. · 2019 [cited by applicant]
US 10390913B2 · Sabina et al. · 2019 [cited by applicant]
US 10453269B2 · Furst · 2019 [cited by applicant]
US 10456043B2 · Atiya et al. · 2019 [cited by applicant]
US 10456229B2 · Fisker et al. · 2019 [cited by applicant]
US 10499793B2 · Ozerov et al. · 2019 [cited by applicant]
US 10504386B2 · Levin et al. · 2019 [cited by applicant]
US 10507087B2 · Elbaz et al. · 2019 [cited by applicant]
US 10517482B2 · Sato et al. · 2019 [cited by applicant]
US 10695150B2 · Kopelman et al. · 2020 [cited by applicant]
US 10708574B2 · Furst et al. · 2020 [cited by applicant]
US 10772506B2 · Atiya et al. · 2020 [cited by applicant]
US 10813727B2 · Sabina et al. · 2020 [cited by applicant]
US 10888399B2 · Kopelman et al. · 2021 [cited by applicant]
US 10952816B2 · Kopelman · 2021 [cited by applicant]
US 10980613B2 · Shanjani et al. · 2021 [cited by applicant]
US 11013581B2 · Sabina et al. · 2021 [cited by applicant]
US D925739S · Shalev et al. · 2021 [cited by applicant]
US 20100036682A1 · Trosien et al. · 2010 [cited by applicant]
US 20100159412A1 · Moss et al. · 2010 [cited by applicant]
US 20130308846A1 · Chen · 2013 [cited by examiner]
US 20140071126A1 · Barneoud · 2014 [cited by examiner]
US 20140172392A1 · Eldershaw et al. · 2014 [cited by applicant]
US 20140227655A1 · Andreiko et al. · 2014 [cited by applicant]
US 20160175068A1 · Cai · 2016 [cited by examiner]
US 20170169562A1 · Somasundaram et al. · 2017 [cited by applicant]
US 20170304005A1 · Maino · 2017 [cited by examiner]
US 20180028294A1 · Azernikov · 2018 [cited by examiner]
US 20180279975A1 · Dekel · 2018 [cited by examiner]
US 20180360567A1 · Xue et al. · 2018 [cited by applicant]
US 20190015177A1 · Elazar et al. · 2019 [cited by applicant]
US 20190029784A1 · Moalem et al. · 2019 [cited by applicant]
US 20190102880A1 · Parpara et al. · 2019 [cited by applicant]
US 20190175314A1 · Lagardere et al. · 2019 [cited by applicant]
US 20190269485A1 · Elbaz · 2019 [cited by examiner]
US 20190348181A1 · Jameel · 2019 [cited by applicant]
US 20190388193A1 · Saphier et al. · 2019 [cited by applicant]
US 20190388194A1 · Yossef et al. · 2019 [cited by applicant]
US 20200066391A1 · Sachdeva et al. · 2020 [cited by applicant]
US 20200143541A1 · Wang et al. · 2020 [cited by applicant]
US 20200281689A1 · Yancey et al. · 2020 [cited by applicant]
US 20200281700A1 · Kopelman et al. · 2020 [cited by applicant]
US 20200281702A1 · Kopelman et al. · 2020 [cited by applicant]
US 20200315434A1 · Kopelman et al. · 2020 [cited by applicant]
US 20200349698A1 · Minchenkov et al. · 2020 [cited by applicant]
US 20200349705A1 · Minchenkov et al. · 2020 [cited by applicant]
US 20200372705A1 · Hershkovich et al. · 2020 [cited by applicant]
US 20200383752A1 · Willers et al. · 2020 [cited by applicant]
US 20200404243A1 · Saphier et al. · 2020 [cited by applicant]
US 20210030503A1 · Shalev et al. · 2021 [cited by applicant]
US 20210059796A1 · Weiss et al. · 2021 [cited by applicant]
US 20210068773A1 · Moshe et al. · 2021 [cited by applicant]
US 20210121049A1 · Rudnitsky et al. · 2021 [cited by applicant]
US 20210128281A1 · Peleg · 2021 [cited by applicant]
US 20210137653A1 · Saphier et al. · 2021 [cited by applicant]
US 20210196152A1 · Saphier et al. · 2021 [cited by applicant]
US 20210353152A1 · Saphier et al. · 2021 [cited by applicant]
US 20220117480A1 · Kaji et al. · 2022 [cited by applicant]
CN 110013328A · 2019 [cited by applicant]
EP 3620130A1 · 2020 [cited by applicant]
WO 2018022752A1 · 2018 [cited by applicant]
Isola P., et al., “Image-to-image Translation With Conditional Adversarial Networks”, Nov. 26, 2018, 17 pages. [cited by applicant]