Sdc U.S. Smilepay Spv

Smiledirectclub LLC

Josh Long

Christopher Yancey

John Dargis

Tony Solarek

Clete Culp

Andrew Wright

Jordan Katzman

Tim Wucher

Cherie Wilson

Roland Harris

Chris Sorrells

Daniel Pfeffer

Ian Kitching

A fixture plate includes a base having a contact face configured to support a dental model having a material formed thereon. The material includes an aligner material portion and an excess material portion. The fixture plate includes one or more channels formed in the contact face. The fixture plate includes a bore extending through the base from a bottom opening to the contact face. A portion of the bore located along the bottom opening is configured to couple with a hose of a vacuum system configured to generate a suction force at the contact face via the one or more channels. The suction force is applied to the dental model and at least part of the excess material portion to retain the dental model and the material formed thereon against the contact face.

Dental model holding system

Systems and methods for trimming dental aligners include a cut line system for identifying a first point and a second point based on a line around tooth (LAT) for a tooth of a model representative of a dentition of a user, where the first point is disposed on a tooth-gingiva interface of the tooth. The cut line system defines a cut plane at a distance from the first point toward the second point, where the cut plane intersects a line between the first point and the second point, identifies a plurality of points on the LAT based on the cut plane, defines a cut line based on the plurality of points on the LAT and the first point, and controls a cutting system to cut the dental aligner along the cut line.

Systems and methods for trimming dental aligners

Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images of dental impressions include a model training system that provides a machine learning model using training image(s) of a dental impression of a respective dental arch and a 3D training model of the respective dental arch. A model generation system receives first image(s) of a first dental impression of a user's dental arch and second image(s), which may be of the first dental impression or a second dental impression of the dental arch. The model generation system generates a first and second 3D model of the dental arch by applying the first image(s) and second image(s) to the machine learning model.

Systems and methods for constructing a three-dimensional model from two-dimensional images

A method for analyzing a quality of a dental aligner includes receiving, by a processor, a digital dental aligner generated based on a fabricated dental aligner. The method also includes analyzing, by the processor, the digital dental aligner to identify a quality characteristic of the fabricated dental aligner. The method also includes flagging, by the processor, the fabricated dental aligner based on the identified quality characteristic.

Systems and methods for intraoral device quality control

Described herein are systems and methods for marking a dental aligner. A method for marking a dental aligner includes receiving a digital model corresponding to a dental aligner. The digital model includes a dental arch comprising a plurality of teeth. The method further includes determining whether a section of teeth on a right side or a left side of the dental arch includes flatter occlusal surfaces and selecting the section with the flatter occlusal surfaces, identifying surfaces on the teeth of the selected section that are flat relative to other surfaces on the teeth of the selected section, determining a line of best fit between the flat surfaces, and marking the dental aligner with a marking based on the line of best fit.

Systems and methods for selecting and marking a location on a dental aligner

Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images of dental impressions include a model training system that provides a machine learning model using training image(s) of a dental impression of a respective dental arch and a 3D training model of the respective dental arch. A model generation system receives first image(s) of a first dental impression of a user's dental arch and second image(s), which may be of the first dental impression or a second dental impression of the dental arch. The model generation system generates a first and second 3D model of the dental arch by applying the first image(s) and second image(s) to the machine learning model. A model merging system merges the first 3D model and the second 3D model to generate a merged model of the dental arch.

Described herein are systems and methods for marking models for dental aligner fabrication. A method for producing a physical model of teeth including a three-dimensional marking includes receiving a first digital model of teeth in an alignment position and selecting a location for marking a physical model of the teeth in the alignment position with a three-dimensional marking, the physical model to be fabricated based on the first digital model. The method also includes generating a second digital model of the teeth in the alignment position based on the first digital model, the second digital model representing the physical model and including the three-dimensional marking at the marking location, and using a three-dimensional fabrication method to fabricate the physical model including the three-dimensional marking from the second digital model.

Systems and methods for marking models for dental aligner fabrication

A fixture plate includes a base having a contact face configured to support a dental model having a model identifier on a bottom surface. A bore extends through the base to one or more channels formed in the contact face and that extend from the bore. A viewing port extends through the base and has a transparent material inserted therein to seal the viewing port at the contact face. The viewing port and the transparent material enable the model identifier to be accessed from underneath the contact face when the dental model is on the contact face. A protrusion extends from the contact face and is configured to interface with an aperture of the dental model to retain the dental model in a specific orientation. The channels are configured to provide a suction force applied through the bore to hold the dental model against the contact face.

Technologies for merging three-dimensional models of dental impressions include a computing device that generates multiple three-dimensional models that are each indicative of a dental impression of a user's dental arch. The models may be generated by scanning the dental impressions. The computing device determines whether a model is indicative of the complete anatomy of the user's arch and, if not, merges multiple models with a merge strategy to generate a merged model. The models may be merged by aligning geometry of the models, selecting geometry from one of the models using the merge strategy, and generating the merged model that includes the selected geometry. The merge strategy may include selecting from the model associated with the dental impression that includes the most detail of the user's anatomy or selecting from the model with the greatest depth.

Technologies for merging three-dimensional models of dental impressions

A method of cutting a dental aligner includes identifying a gingival line in a model representative of a user's dentition where the gingival line is an interface of a teeth portion and a gingival portion of the model, generating a plurality of points in the gingival portion of the model where each point of the plurality of points is generated at a threshold distance from the gingival line, generating a cut line that intersects at least some of the points of the plurality of points, and controlling a cutting system to cut the dental aligner along the cut line.

A computing device for dental impression scan merging includes a processor configured to generate a first model and a second model including a first and second plurality of geometric faces indicative of a first and second dental arch of a user. The processor generates a first point cloud of the first model and a second point cloud of the second model. The processor aligns the first point cloud and the second point cloud. The processor merges the first and second model to generate a merged model where merging the first and second model is based on the alignment of the first point cloud and the second point cloud.

A method for analyzing a quality of a dental aligner includes receiving, by a processor, a digital dental aligner generated based on a fabricated dental aligner, analyzing, by the processor, the digital dental aligner to identify a quality characteristic of the fabricated dental aligner, determining, by the processor, that the quality characteristic is anomalous, and flagging, by the processor, the fabricated dental aligner indicating that the fabricated dental aligner is rejected in response to determining that the quality characteristic is anomalous.

A computing device for dental impression scan merging includes a model manager configured to generate a first three-dimensional model and a second three-dimensional model, and a merge manager configured to merge the first model and the second model. Each model includes a respective plurality of geometric faces indicative of a respective dental impression of a dental arch of a user. Merging the first model and the second model includes aligning the first model and the second model, removing a geometric face of the first model, selecting a geometry of the second model corresponding with the removed geometric face of the first model, and generating a merged model that includes the selected geometry and the geometric faces corresponding to the selected geometry. The merged model is used to manufacture a dental aligner specific to the dental arch of the user and configured to reposition one or more teeth of the user.

Growing community of inventors

Nashville, TN, United States of America

Josh Long