Abstract: Techniques are described for automating the design of dental restoration appliances using neural networks. An example computing device receives transform information associated with a current dental anatomy of a dental restoration patient, provides the transform information associated with the current dental anatomy of the dental restoration patient as input to a neural network trained with transform information indicating placement of a dental appliance component with respect to one or more teeth of corresponding dental anatomies, the dental appliance being used for dental restoration treatment for the one or more teeth, and executes the neural network using the input to produce placement information for the dental appliance component with respect to the current dental anatomy of the dental restoration patient.

Abstract: Machine learning, or geometric deep learning, applied to various dental processes and 5 solutions. In particular, generative adversarial networks apply machine learning to smile design—finished smile, appliance rendering, scan cleanup, restoration appliance design, crown and bridges design, and virtual debonding. Vertex and edge classification apply machine learning to gum versus teeth detection, teeth type segmentation, and brackets and other orthodontic hardware. Regression applies machine learning to coordinate systems, diagnostics, case complexity, and 0 prediction of treatment duration. Automatic encoders and clustering apply machine learning to grouping of doctors, or technicians, and preferences.

Abstract: Methods for generating multiple orthodontic treatment options for a digital 3D model of teeth in malocclusion. The method generates a plurality of different orthodontic treatment plans for the teeth and displays in a user interface the digital 3D model of teeth in malocclusion with a visual indication of each of the plurality of different orthodontic treatment plans. The visual indication of the treatment plans can be overlaid on the digital 3D model of teeth in malocclusion and possibly include aligners, brackets, or a combination of aligners and brackets. A doctor, technician, or other user can then select one of the treatment plans for a particular patient.

Abstract: Methods for generating stages for a portion of orthodontic aligner treatment for a digital 3D model of teeth in malocclusion. The methods generate a subset of stages of setups among a complete set of stages of setups for aligner treatment of the teeth. The subset of stages can be selected from a complete set of stages, based upon a target intermediate setup, or sequentially generated from one stage to the next in the subset. Aligners for the subset of stages of setups can then be manufactured without having to make a complete set of aligners. A method to generate a setup for the aligner treatment compares the digital 3D model of teeth in malocclusion to a plurality of setups for historical cases of teeth in malocclusion that have undergone aligner treatment.

Abstract: Techniques are described for automating the design of dental restoration appliances using neural networks. An example computing device receives transform information associated with a current dental anatomy of a dental restoration patient, provides the transform information associated with the current dental anatomy of the dental restoration patient as input to a neural network trained with transform information indicating placement of a dental appliance component with respect to one or more teeth of corresponding dental anatomies, the dental appliance being used for dental restoration treatment for the one or more teeth, and executes the neural network using the input to produce placement information for the dental appliance component with respect to the current dental anatomy of the dental restoration patient.

Abstract: This disclosure describes a computer-implemented method and system for evaluating, modifying, and determining setups for orthodontic treatment using metrics computed during virtual articulation. The virtual articulation techniques of this disclosure may further be combined with techniques for determining dynamic collision metrics, determining a comfort measurement, determining treatment efficacy, and/or determining dental conditions, such as bruxism. The techniques of this disclosure further include user interface techniques that provide an orthodontist/dentist/technician with information regarding various treatment plans based on metrics gathered during virtual articulation.

Abstract: A system and method of selecting personal protection equipment (PPE) for a worker. The system identifies sets of PPEs and simulates a fitting of the identified PPE sets to the worker. Fitting includes, for each of the identified PPE sets, selecting a three-dimensional computer model for each article of the PPE set, placing the computer model of each of the PPE articles of the PPE set being fitted on a computer model representing the worker, identifying collisions between the computer models as placed, and taking an action based on the identified collisions.

Abstract: A method for evaluating intermediate and final setups for orthodontic treatment. The method includes receiving intermediate and final setups, where each setup is a digital representation of a state of teeth at a particular stage of orthodontic treatment. Scores are computed based upon metrics related to at least some of the states represented by the corresponding setups, and the scores provide an indication of a validity of the corresponding states. The metrics along with an indication of the corresponding scores are displayed in a dashboard in order to provide a visual evaluation of the validity of the setups.

Abstract: A method for generating and reusing digital setups for an orthodontic treatment path. The method receives a digital 3D model of teeth, optionally performs interproximal reduction on the model, and generates an initial treatment path with stages including an initial, final, and intermediate setups. The method divides the initial treatment path into initial steps of feasible motion of the teeth resulting in a final treatment path with setups corresponding with the initial steps. For a treatment redesign, the method computes new steps of feasible motion for only a portion of the initial treatment path and based upon the initial steps, and generates the final treatment path with new setups corresponding with the new steps. The setups can be used to make orthodontic appliances, such as clear tray aligners.

Abstract: Methods for automatically removing collisions between digital mesh objects and moving digital mesh objects between spatial arrangements. The collisions are removed from a set of digital mesh objects using a perturbation method or a mesh deformation method. After removing the collisions, the digital mesh objects are output in a state without collisions between them. The digital mesh objects can be moved between initial and final states based upon motion constraints of the mesh objects and interpolated states of them between the initial and final states. Based upon the constraints and interpolated states, a number of states for movement of the set of digital mesh objects is determined either collectively for the set or individually for each mesh object. The states can be used as digital setups for dental or orthodontic treatment planning.

Abstract: An automated method for generating a final setup for orthodontic treatment. The method includes receiving a digital 3D model of teeth in an initial state. The method computes a scoring function based upon metrics related to the initial state to generate a corresponding score, perturbs the state of the teeth through translations and rotations of a tooth or set of teeth to generate a perturbed state of the teeth, and updates the state of the teeth based upon the score and the perturbed state of the teeth to generate one or more final setups representing a final state of the teeth after the orthodontic treatment.

Abstract: A system and method of selecting personal protection equipment (PPE) for a worker. The system identifies sets of PPEs and simulates a fitting of the identified PPE sets to the worker. Fitting includes, for each of the identified PPE sets, selecting a three-dimensional computer model for each article of the PPE set, placing the computer model of each of the PPE articles of the PPE set being fitted on a computer model representing the worker, identifying collisions between the computer models as placed, and taking an action based on the identified collisions.

Abstract: Methods for tracking gum line changes by comparing digital 3D models of teeth and gingiva taken at different times. The digital 3D models are segmented to digitally identify the teeth from the gingiva, and the segmented digital 3D models are compared to detect gum line changes by determining differences between them relating to the gum line. Gum line changes can also be estimated by comparing one of the digital 3D models with a 3D model having a predicted original location of the gum line. Gum line change maps can be displayed to show the gum line changes determined through the tracking or estimating of changes. The digital 3D models can also be displayed with periodontal measurements placed upon them.

Abstract: A method for generating digital setups for an orthodontic treatment path. The method includes receiving a digital 3D model of teeth, performing interproximal reduction (IPR) on the model and, after performing the IPR, generating an initial treatment path with stages including an initial setup, a final setup, and a plurality of intermediate setups. The method also includes computing IPR accessibility for each tooth at each stage of the initial treatment path, applying IPR throughout the initial treatment path based upon the computed IPR accessibility, and dividing the initial treatment path into steps of feasible motion of the teeth resulting in a final treatment path with setups corresponding with the steps. The setups can be used to make orthodontic appliances, such as clear tray aligners, for each stage of the treatment path.

Abstract: A method for aligning digital 3D models of dental arch pairs, including a mandible and maxilla, to bring them into bite alignment. The method estimates representative planes for the mandible and maxilla 3D models and transforms the models such that the representative planes are each aligned with their respective coordinate systems and shown in a horizontal view. The method also transforms the models such that the mandible and maxilla are each aligned with a same coordinate system and shown in a front view. The digital 3D models are then brought into bite alignment such that the mandible is in occlusion with the maxilla or within a distance near to occlusion. The digital models of the bite-aligned arch pairs can also be transformed or rotated to be shown centered in a front view.

Abstract: Methods for tracking gum line changes by comparing digital 3D models of teeth and gingiva taken at different times. The digital 3D models are segmented to digitally identify the teeth from the gingiva, and the segmented digital 3D models are compared to detect gum line changes by determining differences between them relating to the gum line. Gum line changes can also be estimated by comparing one of the digital 3D models with a 3D model having a predicted original location of the gum line. Gum line change maps can be displayed to show the gum line changes determined through the tracking or estimating of changes. The digital 3D models can also be displayed with periodontal measurements placed upon them.

Abstract: Methods for tracking gum line changes by comparing digital 3D models of teeth and gingiva taken at different times. The digital 3D models are segmented to digitally identify the teeth from the gingiva, and the segmented digital 3D models are compared to detect gum line changes by determining differences between them relating to the gum line. Gum line changes can also be estimated by comparing one of the digital 3D models with a 3D model having a predicted original location of the gum line. Gum line change maps can be displayed to show the gum line changes determined through the tracking or estimating of changes. The digital 3D models can also be displayed with periodontal measurements placed upon them.

Abstract: Methods for tracking gum line changes by comparing digital 3D models of teeth and gingiva taken at different times. The digital 3D models are segmented to digitally identify the teeth from the gingiva, and the segmented digital 3D models are compared to detect gum line changes by determining differences between them relating to the gum line. Gum line changes can also be estimated by comparing one of the digital 3D models with a 3D model having a predicted original location of the gum line. Gum line change maps can be displayed to show the gum line changes determined through the tracking or estimating of changes. The digital 3D models can also be displayed with periodontal measurements placed upon them.

Abstract: At least some embodiments of the present disclosure feature systems and methods for assessing the impact of visual features within a region of a scene. With the input of a visual representation of a scene and at least one selected region within the scene, the system applies a visual attention model to the visual representation to determine visual conspicuity of the at least one selected region. The system computes feature-related data associated with a plurality of features of the at least one selected region. Based on the visual conspicuity and the feature-related data, the system assesses an impact that at least one of the features within the at least one selected region have on the visual conspicuity.

Abstract: A method for aligning digital 3D models of dental arch pairs, including a mandible and maxilla, to bring them into bite alignment. The method estimates representative planes for the mandible and maxilla 3D models and transforms the models such that the representative planes are each aligned with their respective coordinate systems and shown in a horizontal view. The method also transforms the models such that the mandible and maxilla are each aligned with a same coordinate system and shown in a front view. The digital 3D models are then brought into bite alignment such that the mandible is in occlusion with the maxilla or within a distance near to occlusion. The digital models of the bite-aligned arch pairs can also be transformed or rotated to be shown centered in a front view.