Align Technology, Inc.

Shai Farkash

Maayan Moshe

Adi Levin

Moti Ben-Dov

Avi Kopelman

Pavel Agniashvili

Jonathan Coslovsky

Maxim Volgin

Ofer Saphier

Doron Malka

Ran Katz

Edi Fridman

Avraham Zulti

Yossef Atiya

Ido Tishel

Inna Karapetyan

Pavel Veryovkin

Dina Bova

Michael Sabina

Chad Clayton Brown

Assaf Weiss

Ofer Sagi

Abraham Albert Burbea

Alexander Raskhodchikov

Igor Makiewsky

Shai Ayal

Raphael Levy

Eliahou Franklin Nizard

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.

Smart scanning for intraoral scanners

In embodiments set forth herein, an intraoral scanning system includes a first intraoral scanner, a second intraoral scanner, and a computing device wirelessly connected to both the first intraoral scanner and the second intraoral scanner. The computing device receives first intraoral scan data from the first intraoral scanner and generates a first three-dimensional (3D) surface of at least a portion of a first patient's dental arch based on the first intraoral scan data. The computing device further receives second intraoral scan data from the second intraoral scanner and generates a second 3D surface of at least a portion of a second patient's dental arch based on the second intraoral scan data.

Distributed intraoral scanning system

Methods and apparatuses (e.g., systems) for assessing oral health. In some examples, one or more periodontal pockets in a 3D model of a dental arch may be identified. The digital 3D model may be generated from scan data collected from an oral scan, where the scan data may include 3D surface data and one or more of: color image data, near-infrared (NIR) data, and fluorescence imaging data. A periodontal pocket depth may be determined for each periodontal pocket using a trained machine learning model, which may be trained on image data including previous 3D surface data and one or more of: previous color image data, previous NIR data, and previous fluorescence imaging data. An indicator of the determined periodontal pocket depth may be displayed on one or more 2D images and/or the digital 3D model of the subject's dental arch.

Noninvasive multimodal oral assessment systems

Provided herein are devices and methods generating synthetic views of a subject's teeth. Methods and processes are provided to image the subject's teeth with a dental scan. Methods and processes are also provided to automatically 3D render the subject's teeth with the scan images. Methods and apparatuses are also provided to generate simulated synthetic views of the subject's dentition from various perspectives.

Dental panoramic views

In embodiments, a processing device detects a margin line in a model of a preparation from one or more images. The processing device determines, for each segment of a plurality of segments of the margin line, a quality score for the segment. The processing device determines that a segment of the margin line has a quality score that is below a quality threshold, wherein the segment of the margin line was generated based on a first set of images. Responsive to determining that the segment of the margin line has the quality score that is below the quality threshold, the processing devices updates the three-dimensional model of the preparation by replacing a portion of the three-dimensional model associated with the segment of the margin line with image data from at least one of a new image or a second set of images.

Automated detection, generation and/or correction of margin lines in digital models

Dental imaging attachment for a smartphone

A first computing device receives a command to associate the first computing device with an intraoral scanner, the command comprising an identifier. The first computing device wirelessly connects with a second computing device, and sends the identifier to the second computing device. The second computing device wirelessly connects to the intraoral scanner and associates the first computing device with the intraoral scanner. Subsequently, intraoral scan data generated by the first intraoral scanner is sent to the second computing device, the intraoral scan data is processed by the second computing device to generate a three-dimensional surface of a dental site, the three-dimensional surface or a view of the three-dimensional surface of the dental site is sent to the first computing device, and the three-dimensional surface or the view of the three-dimensional surface of the dental site is displayed by the first computing device.

Device pairing for distributed intraoral scanning system

A processing device may receive a plurality of intraoral scans of the patient that were generated by an intraoral scanner, determine a three-dimensional surface of at least a portion of one or more dental arch of the patient using the plurality of intraoral scans, automatically determine whether a restorative dental object is represented in at least one of the three-dimensional surface or one or more intraoral scans of the plurality of intraoral scans, and automatically generate a prescription for treating the one or more teeth based at least in part on at least one of a) a presence or absence of a restorative dental object in at least one of the three-dimensional surface or the one or more intraoral scans or b) a location of the restorative dental object in the one or more dental arch of the patient.

Automatic generation of prosthodontic prescription

A method of generating a 3D model includes: determining a 3D surface comprising a preparation tooth using a first plurality of intraoral scans generated by an intraoral scanner at a first time; receiving one or more additional intraoral scans of the preparation tooth that were generated by the intraoral scanner at a second time; determining a change to one or more portions of the preparation tooth between the three-dimensional surface and the one or more additional intraoral scans; determining, based at least in part on the change to the preparation tooth, whether to use a) the 3D surface, b) data from the one or more additional intraoral scans or c) a combination of the 3D surface and the data from the one or more additional intraoral scans to depict one or more portions of the preparation tooth; and generating the 3D model comprising the preparation tooth.

Automatic determination of workflow for restorative dental procedures

A processing device receives a plurality of intraoral scans of a dental arch. The processing device determines, from the plurality of intraoral scans, a first set of intraoral scans that depict a restorative object and a second set of intraoral scans that fail to depict any restorative object. The processing device generates a multi-resolution three-dimensional model of the dental arch, wherein a first portion of the multi-resolution three-dimensional model is generated from the first set of intraoral scans, has a first resolution and represents the restorative object, and wherein a second portion of the multi-resolution three-dimensional model is generated from the second set of intraoral scans, has a second resolution and represents a remainder of the dental arch, wherein the first resolution is greater than the second resolution.

Automatic generation of multi-resolution 3d model including restorative object

In embodiments, a processing device generates a three-dimensional model of a dental site from scan data, the three-dimensional model comprising a representation of a tooth, wherein a portion of the three-dimensional model comprises an interfering surface that obscures a portion of the tooth. The processing device receives or generates an image of the tooth, wherein the image depicts the interfering surface. The processing device processes the image to generate a modified image, wherein the portion of the tooth that was obscured by the interfering surface in the image is shown in the modified image. The processing device updates the three-dimensional model of the dental site by replacing, using the modified image, the portion of the three-dimensional model that comprises the interfering surface that obscures the portion of the tooth, wherein the portion of the tooth that was obscured in the three-dimensional model is shown in an updated three-dimensional model.

Automated, generation of dental features in digital models

Systems and methods for monitoring a subject's teeth during orthodontic treatment. An input 2D image of the subject's current teeth including a wide angle occlusal view of the subject's upper and/or lower jaw at a current treatment stage can be received. Virtual camera parameters corresponding to the input 2D image can be determined. A rendered 2D image of the subject's teeth can be generated from a 3D model of the subject's upper and/or lower jaw at a planned treatment stage with the virtual camera parameters. Differences between the subject's teeth from the input 2D image and the rendered 2D image using tooth centers can be determined. An indicator indicating the differences can be output.

Tracking orthodontic treatment using teeth images

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.

Noninvasive multimodal oral assessment and disease diagnoses apparatus and method

In embodiments set forth herein, an intraoral scanner comprises a body, a probe at one end of the body, the probe comprising a scanner head, a wireless communication module disposed within the body, one or more optical sensor, and a touchscreen disposed on the body. The one or more optical sensor is to receive light that enters the scanner head and generate intraoral scan data based on the light, wherein the wireless communication module is to wirelessly send the intraoral scan data to a first computing device. The touchscreen is configured to output a plurality of virtual buttons, detect a touch input associated with a virtual button of the plurality of virtual buttons, and provide a signal associated with the touch input of the virtual button to the first computing device.

Wireless intraoral scanner for distributed intraoral scanning system

Methods and systems are described that mark and/or correct margin lines and/or other features of dental sites. In one example a three-dimensional model of a dental site is generated from intraoral scan data of the dental site, the three-dimensional model comprising a representation of a preparation tooth. An image of the preparation tooth is received or generated. Data from the image is processed using a trained machine learning model that has been trained to identify margin lines of preparation teeth, wherein the trained machine learning model outputs a probability map comprising, for each pixel in the image, a probability that the pixel depicts a margin line. The three-dimensional model of the dental site is then updated by marking the margin line on the representation of the preparation tooth based on the probability map.

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Hod HaSharon, Israel

Shai Farkash