Abstract:
Provided herein are systems and methods for determining if a 3D tooth model requires trimming or removal of incomplete or missing data (e.g., gingiva covering a portion of a tooth such as a molar). A patient's dentition may be scanned and/or segmented. Raw 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 classifier can identify and/or output probability that the 3D tooth model requires trimming. Trimming of the 3D tooth model can be implemented without human intervention.
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:
Provided herein are systems and methods for determining if a 3D tooth model requires trimming or removal of incomplete or missing data (e.g., gingiva covering a portion of a tooth such as a molar). A patient's dentition may be scanned and/or segmented. Features of the patient's teeth can be determined, including a tooth center point of at least three of the patient's teeth. The features of the patient's teeth are used to access a parametric model. A trim plane normal vector is identified for a distal tooth. Trimming of the 3D tooth model is based on the trim plane normal vector.
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:
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:
Provided herein are orthodontic devices and methods for patients with missing or ectopic teeth. Methods and processes are provided to properly number the teeth of a patient's arch after a dental scan. Methods and processes are also provided to automatically detect missing or ectopic teeth after a dental scan. Methods of designing and manufacturing the aligner are also provided.
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:
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.