Align Technology, Inc.

Assaf Weiss

Maayan Moshe

Avi Kopelman

Ofer Saphier

Michael Sabina

Eric E Kuo

Shai Ayal

Doron Malka

Gilad Elbaz

Ido Tishel

Eliahou Franklin Nizard

Yossef Atiya

Erez Lampert

Chad Clayton Brown

Shai Farkash

Pavel Agniashvili

Moti Ben-Dov

Maxim Volgin

Alexander Raskhodchikov

Igor Makiewsky

Yingjie Li

Phillip Thomas Harris

Maurice K Carrier

Ozi Marom

Methods and apparatuses for generating and displaying a model of a subject's teeth. Described herein are intraoral scanning methods and apparatuses for generating a three-dimensional model of a subject's intraoral region (e.g., teeth). These methods and apparatuses may be used for identifying and evaluating lesions, caries and cracks in the teeth.

Intraoral scanning apparatus

Described herein are intraoral scanning apparatuses comprising visible light and near-infrared (near-IR) light images from a patient's dentition. These apparatuses may display a 3D model of the patient's dental arch and a plurality of images of the patient's dental arch taken from different angles and positions relative to the patient's dental arch, and may both generate and display a two-dimensional (2D) image based on a relative angle and position between the indicator relative to the 3D model of the patient's dental arch.

Diagnostic intraoral scanning apparatuses

Intraoral scanning systems configured to perform computer-implemented methods for identifying dental features. The methods may include engaging a trained machine learning network to identify one or more dental features in one or more regions of a patient's dentition. Each of the dental features may be present in at least one of multiple records. Each of the records may include multiple images of the patient's dentition and may be taken with a different imaging modality. The confidence score may be determined or adjusted using aD model of the patient's dentition. The confidence score may be determined or adjusted based on the region of the patient's dentition within each record. The methods may include displaying an indicator of each dental feature that has a confidence score that is above a threshold on theD model of the patient's dentition, and modifying the display as a user adjusts the threshold.

Diagnostic intraoral methods and apparatuses

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

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

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.

Automated detection, generation and/or correction of dental features in digital models

Intraoral scanning systems for displaying 3D models of a patient's dental arch and near-IR images from the dental arch. These systems may include a wand with one or more image sensors and processors for processing the 3D models and near-IR information. The 3D models may include surface (e.g., color) information and the near-IR images may include information on internal structures, including enamel and dentin.

Intraoral scanning systems

System for scanning a subject's teeth. Described herein are intraoral scanning apparatuses for generating a three-dimensional model of a subject's intraoral region (e.g., teeth). These apparatuses may be used for identifying and evaluating lesions, caries and cracks in the teeth.

Methods and apparatuses for taking, using and displaying three-dimensional (3D) volumetric models of a patient's dental arch. A 3D volumetric model may include surface (e.g., color) information as well as information on internal structure, such as near-infrared (near-IR) transparency values for internal structures including enamel and dentin.

Methods and apparatuses for forming a model of a subject's teeth

Methods and apparatuses for generating a model of a subject's teeth. Described herein are intraoral scanning methods and apparatuses for generating a three-dimensional model of a subject's intraoral region (e.g., teeth) including both surface features and internal features. These methods and apparatuses may be used for identifying and evaluating lesions, caries and cracks in the teeth. Any of these methods and apparatuses may use minimum scattering coefficients and/or segmentation to form a volumetric model of the teeth.

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Yavne, Israel

Assaf Weiss