Abstract: Methods and systems for improving segmentation of a digital model of a patient's dentition into component teeth.

Abstract: Methods and apparatuses for automatic treatment planning, including recommendation systems, quality assurance, error prevention, text mining, text matching, and treatment planning optimization.

Abstract: A computer-implemented method for virtually representing an orthodontic treatment outcome using automated detection of facial and dental reference objects is disclosed herein. The computer-implemented method may involve modeling initial positions of an orthodontic patient's teeth in a three-dimensional (3D) virtual model and determining the effect of application of various force systems applied through an orthodontic treatment plan on the patient's teeth. Images of the patient's face may be used to identify facial reference objects. Dental reference objects of the patient's dentition may be identified from the 3D virtual model. A relationship between the facial reference objects and the dental reference objects may form the basis of modifications to the orthodontic treatment plan and/or modeling final orthodontic positions of the orthodontic treatment plan.

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 may include: receiving an image of a mouth region of a patient's face; extracting teeth contours within the image of the mouth region of the patient's face; locating a mouth opening within the image of the mouth region of the patient's face; extracting the tooth contours from a 3D model of the patient's teeth; and aligning the tooth contours from the 3D model with the tooth contours of the teeth within the image of the mouth region of the patient's face.

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 computer-implemented method for virtually representing an orthodontic treatment outcome using automated detection of facial and dental reference objects is disclosed herein. The computer-implemented method may involve modeling initial positions of an orthodontic patient's teeth in a three-dimensional (3D) virtual model and determining the effect of application of various force systems applied through an orthodontic treatment plan on the patient's teeth. Images of the patient's face may be used to identify facial reference objects. Dental reference objects of the patient's dentition may be identified from the 3D virtual model. A relationship between the facial reference objects and the dental reference objects may form the basis of modifications to the orthodontic treatment plan and/or modeling final orthodontic positions of the orthodontic treatment plan.

Abstract: A computer-implemented method for generating a virtual depiction of an orthodontic treatment of a patient is disclosed herein. The computer-implemented method may involve gathering a three-dimensional (3D) model modeling the patient's dentition at a specific treatment stage of an orthodontic treatment plan. An image of the patient's face and dentition may be gathered. A first set of reference points modeled on the 3D model of the patient's dentition and a second set of reference points represented on the dentition of the image of the patient may be received. The image of the patient's dentition may be projected into a 3D space to create a projected 3D model of the image of the patient's dentition. Based on a comparison of the first reference points and projections of the second set of reference points, a modified image of the patient may be constructed and/or modeled.

Abstract: A method may include: receiving an image of a mouth region of a patient's face; extracting teeth contours within the image of the mouth region of the patient's face; locating a mouth opening within the image of the mouth region of the patient's face; extracting the tooth contours from a 3D model of the patient's teeth; and aligning the tooth contours from the 3D model with the tooth contours of the teeth within the image of the mouth region of the patient's face.