Abstract: The example systems, methods, and/or computer-readable media described herein help with design of highly accurate models of un-erupted or partially erupted teeth and help fabricate of aligners for un-erupted or partially erupted teeth. Automated agents that use machine learning models to parametrically represent three-dimensional (3d) virtual representations of teeth as 3D descriptors in a 3D descriptor space are provided herein. In some implementations, the automated agents described herein provide instructions to fabricate aligners for at least partially un-erupted teeth using representative 3D descriptor(s) of a tooth type.

Abstract: The example systems, methods, and/or computer-readable media described herein help with design of highly accurate models of un-erupted or partially erupted teeth and help fabricate of aligners for un-erupted or partially erupted teeth. Automated agents that use machine learning models to parametrically represent three-dimensional (3d) virtual representations of teeth as 3D descriptors in a 3D descriptor space are provided herein. In some implementations, the automated agents described herein provide instructions to fabricate aligners for at least partially un-erupted teeth using representative 3D descriptor(s) of a tooth type.

Abstract: The example systems, methods, and/or computer-readable media described herein help with design of highly accurate models of un-erupted or partially erupted teeth and help fabricate of aligners for un-erupted or partially erupted teeth. Automated agents that use machine learning models to parametrically represent three-dimensional (3d) virtual representations of teeth as 3D descriptors in a 3D descriptor space are provided herein. In some implementations, the automated agents described herein provide instructions to fabricate aligners for at least partially un-erupted teeth using representative 3D descriptor(s) of a tooth type.

Abstract: The example systems, methods, and/or computer-readable media described herein help with design of highly accurate models of un-erupted or partially erupted teeth and help fabricate of aligners for un-erupted or partially erupted teeth. Automated agents that use machine learning models to parametrically represent three-dimensional (3d) virtual representations of teeth as 3D descriptors in a 3D descriptor space are provided herein. In some implementations, the automated agents described herein provide instructions to fabricate aligners for at least partially un-erupted teeth using representative 3D descriptor(s) of a tooth type.

Abstract: The example systems, methods, and/or computer-readable media described herein help with design of highly accurate models of un-erupted or partially erupted teeth and help fabricate of aligners for un-erupted or partially erupted teeth. Automated agents that use machine learning models to parametrically represent three-dimensional (3d) virtual representations of teeth as 3D descriptors in a 3D descriptor space are provided herein. In some implementations, the automated agents described herein provide instructions to fabricate aligners for at least partially un-erupted teeth using representative 3D descriptor(s) of a tooth type.

Abstract: The example systems, methods, and/or computer-readable media described herein help with design of highly accurate models of un-erupted or partially erupted teeth and help fabricate of aligners for un-erupted or partially erupted teeth. Automated agents that use machine learning models to parametrically represent three-dimensional (3d) virtual representations of teeth as 3D descriptors in a 3D descriptor space are provided herein. In some implementations, the automated agents described herein provide instructions to fabricate aligners for at least partially un-erupted teeth using representative 3D descriptor(s) of a tooth type.

Abstract: The example systems, methods, and/or computer-readable media described herein help with design of highly accurate models of un-erupted or partially erupted teeth and help fabricate of aligners for un-erupted or partially erupted teeth. Automated agents that use machine learning models to parametrically represent three-dimensional (3d) virtual representations of teeth as 3D descriptors in a 3D descriptor space are provided herein. In some implementations, the automated agents described herein provide instructions to fabricate aligners for at least partially un-erupted teeth using representative 3D descriptor(s) of a tooth type.

Abstract: Provided herein are methods and apparatuses for recommending tooth leveling (e.g., one or more of anterior leveling, posterior leveling, and arch-shape recommendations) for orthodontic devices and methods for patients. Factors involved in the leveling of teeth can include symmetry, doctor preferences, preferences regarding gender, the country in which the patient is being treated, and other issues related to the aesthetics of the mouth and arch shape. The device can comprise an aligner configured to fit over a patient's teeth. Methods of designing and manufacturing aligners based on leveling recommendations are also provided.

Abstract: A system for determining the relative displacement of a rigid object is described herein. In one embodiment, the system includes three data sources positioned on an object. The data sources are configured to transmit data relating to positional displacement of the object. Each data source has predefined movement parameters based on the position of each data source on the object. In one embodiment, the system further includes a receiver unit configured to display positional information relating to the object based on the data received from each data source. The positional information represents a single valid solution set generated in part by eliminating positional movements that exceed the predefined movement parameters.

Abstract: A system for determining the relative displacement of a rigid object is described herein. In one embodiment, the system includes three data sources positioned on an object. The data sources are configured to transmit data relating to positional displacement of the object. Each data source has predefined movement parameters based on the position of each data source on the object. In one embodiment, the system further includes a receiver unit configured to display positional information relating to the object based on the data received from each data source. The positional information represents a single valid solution set generated in part by eliminating positional movements that exceed the predefined movement parameters.