公开(公告)号：US20220262007A1

公开(公告)日：2022-08-18

申请号：US17671406

申请日：2022-02-14

Applicant: Align Technology, Inc.

Inventor： Christopher E. CRAMER ,  Pavel AGNIASHVILI ,  Chad Clayton BROWN

IPC: G06T7/162 ,  G06N3/08 ,  G06T17/20 ,  G06T7/11 ,  G06V10/774 ,  G06V10/82 ,  A61C13/34

Abstract: Provided herein are systems and methods for automatically segmenting a 3D model of a patient's teeth. A patient's dentition may be scanned. The scan data may be converted into a 3D model, including a graph-based representation of the 3D model. The graph-based representation can be input into a machine learning model to train the machine learning model to segment the 3D model into individual dental components. Trained machine learning models can also be used to segment graph-based representations of a 3D model of a patient's teeth.

公开(公告)号：US20210074061A1

公开(公告)日：2021-03-11

申请号：US17013518

申请日：2020-09-04

Applicant: Align Technology, Inc.

Inventor： Chad C. BROWN ,  Yun GAO ,  Pavel AGNIASHVILI ,  Avraham ZULTI ,  Jonathan COSLOVSKY ,  Christopher E. CRAMER ,  Roman GUDCHENKO ,  Ofer SAPHIER ,  Adi LEVIN ,  Maayan MOSHE ,  Doron MALKA

IPC: G06T17/20 ,  G06T19/20 ,  G16H30/20 ,  G06N20/00

Abstract: Methods and apparatuses (including systems and devices) for modifying a three-dimensional (3D) model of a subject's oral cavity to determine individual components such as teeth, gingiva, tongue, palate, etc. In some implementations one or more automated machine learning agents may modify one or more subsets of 3D models of the subject's oral cavity using height map data to identify, segment and/or modify to mesh regions of a 3D model constructed from a plurality of 2D images of the subject's dental cavity.

公开(公告)号：US20240029265A1

公开(公告)日：2024-01-25

申请号：US18305323

申请日：2023-04-21

Applicant: Align Technology, Inc.

Inventor： Chad C. BROWN ,  Yun GAO ,  Pavel AGNIASHVILI ,  Avraham ZULTI ,  Jonathan COSLOVSKY ,  Christopher E. CRAMER ,  Roman GUDCHENKO ,  Ofer SAPHIER ,  Adi LEVIN ,  Maayan MOSHE ,  Doron MALKA

IPC: G06T7/11 ,  G06T7/00 ,  G16H30/20 ,  G06N20/00 ,  G06T17/20 ,  G06T19/20 ,  G06N3/045

CPC classification number: G06T7/11 ,  G06T7/0012 ,  G16H30/20 ,  G06N20/00 ,  G06T17/205 ,  G06T19/20 ,  G06N3/045 ,  G06T2207/20084 ,  G06T2207/30036 ,  G06T2207/20081 ,  G06T2210/41 ,  G06T2219/2012

Abstract: Methods and apparatuses (including systems and devices), including computer-implemented methods for segmenting, correcting and/or modifying a three-dimensional (3D) model of a subject's oral cavity to determine individual components such as teeth, gingiva, tongue, palate, etc., that may be selective and/or collectively digitally manipulated. In some implementations, artificial intelligence uses libraries of labeled 2D images and 3D dental models to learn how to segment a 3D dental model of a subject's oral cavity using 2D images, height map and/or other data and projection values that relate the 2D images to the 3D model. As noted herein, the dental classes can include a variety of intra-oral and extra-oral objects and can be represented as binary values, discrete values, a continuum of height map data, etc. In some implementations, several dental classes are predicted concurrently.

公开(公告)号：US20210073998A1

公开(公告)日：2021-03-11

申请号：US17013513

申请日：2020-09-04

Applicant: Align Technology, Inc.

Inventor： Chad C. BROWN ,  Yun GAO ,  Pavel AGNIASHVILI ,  Avraham ZULTI ,  Jonathan COSLOVSKY ,  Christopher E. CRAMER ,  Roman GUDCHENKO ,  Ofer SAPHIER ,  Adi LEVIN ,  Maayan MOSHE ,  Doron MALKA

IPC: G06T7/11 ,  G06T7/00 ,  G06N3/04

Abstract: Methods and apparatuses (including systems and devices), including computer-implemented methods for segmenting, correcting and/or modifying a three-dimensional (3D) model of a subject's oral cavity to determine individual components such as teeth, gingiva, tongue, palate, etc., that may be selective and/or collectively digitally manipulated. In some implementations, artificial intelligence uses libraries of labeled 2D images and 3D dental models to learn how to segment a 3D dental model of a subject's oral cavity using 2D images, height map and/or other data and projection values that relate the 2D images to the 3D model. As noted herein, the dental classes can include a variety of intra-oral and extra-oral objects and can be represented as binary values, discrete values, a continuum of height map data, etc. In some implementations, several dental classes are predicted concurrently.