Sdc U.S. Smilepay Spv

Andrew Wright

Christopher Yancey

Josh Long

Jordan Katzman

Tim Wucher

John Dargis

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

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.

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.

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Nashville, TN, United States of America

Andrew Wright