Abstract:
Methods for generating orthodontic models having bite adjustment structures may include generating orthodontic treatment plan comprising a plurality of stages by positioning a plurality of digital bite adjustment structures on a corresponding plurality of anterior digital teeth of a digital model of a jaw at a first stage of a treatment plan, adjusting the position of the plurality of digital bite adjustment structures on the corresponding plurality of anterior digital teeth of the digital model of the jaw at a second stage of the treatment plan according to changes to the digital model of the jaw between the first stage of the treatment plan and the second stage of the treatment plan, and providing the digital model of the jaw for fabrication of physical models corresponding to the jaw at the first and the second stages of the treatment plan for formation of appliances thereover.
Abstract:
Systems, methods, and computer-readable media for identifying and facilitating review of outlier treatment plans. A method includes receiving an initial three-dimensional (3D) model of an initial arrangement of a patient’s teeth and generating a first final 3D model of a first final arrangement of the patient’s teeth based on the initial 3D model of the initial arrangement of the patient’s teeth. The method further includes comparing the first final arrangement of the patient’s teeth with a set of a plurality of final arrangements of teeth from previous treatment plans of past patients and determining whether the first final arrangement of the patient’s teeth satisfies one or more outlier criteria based on the comparing. Responsive to determining that the first final arrangement of the patient’s teeth satisfies the one or more outlier criteria, an orthodontic treatment plan comprising the first final 3D model of the first final arrangement of the patient’s teeth is classified as a clinical risk.
Abstract:
A method includes to receive, via a computing device, data representing a plurality of teeth, identify data indicating which of the plurality of teeth are unerupted or erupting, predict at least one characteristic of a tooth of the unerupted or erupting teeth after they have fully erupted using one or more tooth eruption prediction factors, generate new data representing the unerupted or erupting teeth in multiple states of eruption based upon the predicted at least one characteristic of the fully erupted teeth, and generate a series of incremental tooth arrangements with the new data to define a proposed orthodontic treatment based on the new data representing the unerupted or erupting teeth in multiple states of eruption.
Abstract:
In one aspect, an orthodontic appliance can include a shell having a plurality of cavities shaped to receive a patient's teeth. The shell can include an exterior layer and an interior layer having a stiffness less than a stiffness of the exterior layer. A discontinuity can be formed in the exterior layer.
Abstract:
A method includes to receive, via a computing device, data representing a plurality of teeth, identify data indicating which of the plurality of teeth are unerupted or erupting, predict at least one characteristic of a tooth of the unerupted or erupting teeth after they have fully erupted using one or more tooth eruption prediction factors, generate new data representing the unerupted or erupting teeth in multiple states of eruption based upon the predicted at least one characteristic of the fully erupted teeth, and generate a series of incremental tooth arrangements with the new data to define a proposed orthodontic treatment based on the new data representing the unerupted or erupting teeth in multiple states of eruption.
Abstract:
Methods for and media with instruction to cause acquiring known dimensions of a tooth, applying a multivariant regression model using the known dimensions to calculate projected dimensions of the unerupted or erupting tooth, customizing a standard virtual geometry and/or a predefined virtual geometry using the projected dimensions of the unerupted or erupting tooth, and inserting the customized virtual geometry into a virtual model of the patient's jaw, and planning the movement of the teeth of the patient and designing a series of removable orthodontic aligners using the virtual model, the series of removable orthodontic aligners configured to be worn by the patient to incrementally align the teeth according to the planned movement.
Abstract:
Computer readable media for predicting a tooth shape for at least partially un-erupted teeth and dental appliances formed therefrom. In some examples, methods include generating orthoscopic views of virtual representations of an identified tooth type in different orthogonal directions, representing bounding shapes around the orthoscopic views, and applying principal component analysis on the bounding shapes to predict a tooth shape. In some examples, methods include generating a spherical harmonic signature for virtual representations of an identified tooth type, calculating a distance between spherical harmonic signatures to predict the tooth shape. The predicted tooth shape of the at least partially un-erupted tooth may be incorporated into virtual dentition model(s) of a dentition in accordance with an orthodontic treatment plan for treating the dentition.
Abstract:
A series of appliances including a first shell and a second shell can be designed to incrementally implement a treatment plan. The first and second shells can have cavities designed to receive teeth of a jaw. A first number of bite adjustment structures can be formed of a same material as the first shell, extending therefrom and designed to interface with teeth of a second jaw. The first number of bite adjustment structures can have a first shape and location specific to a first stage of the treatment plan. A second number of bite adjustment structures can be formed of a same material as the second shell, extending therefrom and designed to interface with teeth of the second jaw. The second number of bite adjustment structures can have a second shape and location, different than the first shape and location, specific to a second stage of the treatment plan.
Abstract:
Provided herein are systems and methods for detecting the eruption state (e.g., tooth type and/or eruption status) of a target tooth. A patient's dentition may be scanned and/or segmented. A target tooth may be identified. Dental features, principal component analysis (PCA) features, and/or other features may be extracted and compared to those of other teeth, such as those obtained through automated machine learning systems. A detector can identify and/or output the eruption state of the target tooth, such as whether the target tooth is a fully erupted primary tooth, a permanent partially erupted/un-erupted tooth, or a fully erupted permanent tooth.
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.