Abstract: A system includes one or more processors coupled to non-transitory memory, and the one or more processors are configured to receive a first image representing at least a portion of a mouth of a user, execute a first machine-learning architecture trained to generate a set of features from the first image, determine, based on the set of features, that the first image satisfies at least one criteria for executing a second machine-learning architecture based on the first image, and generate, based on the first image satisfying the at least one criteria, a prompt indicating feedback for capturing a second image representing at least a second portion of the mouth of the user.

Abstract: A method for orthodontic treatment includes providing a first set of aligners to a user. The first set of aligners includes a first aligner, a second aligner, and a third aligner configured to move a tooth of a user. The first aligner, the second aligner, and the third aligner are created using a single physical dental model and are substantially the same shape. The first aligner has a first thickness, the second aligner has a second thickness, and the third aligner has a third thickness. The first thickness is different than the second thickness and the third thickness, and the second thickness is at least substantially equivalent to the third thickness.

Abstract: A system includes a model generation system configured to receive one or more dental images corresponding to a dental arch of a user, generate a three-dimensional (3D) model of at least a portion of the dental arch of the user by applying the one or more dental images to a machine learning model to generate the 3D model where the machine learning model is trained based on at least one of one or more training images or one or more three-dimensional (3D) training models, and output the 3D model of the at least the portion of the dental arch to one or more computing devices.

Abstract: Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images of dental impressions include a model training system that provides a machine learning model using training image(s) of a dental impression of a respective dental arch and a 3D training model of the respective dental arch. A model generation system receives first image(s) of a first dental impression of a user's dental arch and second image(s), which may be of the first dental impression or a second dental impression of the dental arch. The model generation system generates a first and second 3D model of the dental arch by applying the first image(s) and second image(s) to the machine learning model.

Abstract: Systems, methods, and computer readable medium of visualizing a treatment of teeth includes capturing, by a user device, a representation representing one or more teeth of a user via a camera of a user device, transmitting, by the user device, the representation to a treatment planning system, receiving, by the user device, a graphical visualization of a treatment plan for moving the one or more teeth of the user from the treatment planning system, the graphical visualization generated based on the representation, displaying, by the user device, the graphical visualization, wherein the graphical visualization comprises a three-dimensional (3D) representation corresponding to the one or more teeth of the user and an interactive object associated with the treatment plan.

Abstract: Systems and methods for determining movement of teeth include receiving a first 3D representation of a dentition comprising a plurality of teeth of a patient in an initial position, the 3D representation comprising a plurality of tooth representations including a plurality of points representing surfaces of a respective tooth of the dentition, generating, for each tooth representation, a compressed tooth representation using a geometric encoder model trained to compress the 3D representation of the detention, determining tooth movements of the plurality of teeth of the dentition from the initial position to a final position by applying each compressed tooth representation to a final position model trained to output movement of teeth of a dentition from initial positions to final positions, generating another 3D representation of the dentition comprising the plurality of teeth of the patient in the final position based on applying the tooth movements to the first 3D representations.

Abstract: A system includes one or more processors and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to receive a two-dimensional (2D) representation provided by a user device where the 2D representation represents one or more teeth of a user, generate a three-dimensional (3D) representation of the one or more teeth of the user based on the 2D representation, generate a treatment plan for moving the one or more teeth of the user based on the 3D representation, and provide a graphical visualization of the treatment plan to the user device, wherein the graphical visualization is configured to enable the user to make a selection.

Abstract: A method of visualizing a treatment of teeth includes maintaining a final position model trained to output movement of teeth from initial to final positions, receiving from a user device a first representation comprising teeth of a user in an initial position where the first representation is based on a 2D image transmitted from the user device, determining tooth movements of the teeth from the initial position to a final position using to the final position model, receiving by the user device a graphical visualization of a treatment plan for moving the teeth of the user where the graphical visualization is generated based on the final position and the treatment plan is suitable for correcting the user's malocclusion, and displaying by the user device the graphical visualization where the graphical visualization comprises a three-dimensional (3D) representation corresponding to the teeth of the user.

Abstract: Systems and methods for generating a 3D model of a dentition are disclosed herein. A method includes generating a first 3D model of a dentition including a plurality of model teeth. The method includes receiving at least one digital representation comprising patient teeth. The method includes determining a virtual camera parameter. The virtual camera parameter corresponds with a camera used to capture the digital representation. The method includes comparing, based on the virtual camera parameter, a first position of a model tooth with a position of a corresponding patient tooth of the digital representation. The method includes moving the model tooth from the first position to a second position. The second position is based on the position of the corresponding patient tooth. The method includes generating a second 3D model comprising the model tooth of the first 3D model in the second position.

Abstract: Systems and methods disclosed herein use a first machine learning architecture and a second machine learning architecture where the first machine learning architecture executes on a first processor and receives a first image representing a mouth of a user, determines user feedback for outputting to the user based on a first machine learning model, and outputs the user feedback for capturing a second image representing the mouth of the user. The second machine learning architecture executes on a second processor and receives the first image and the second image, and generates a 3D model of at least a portion of a dental arch of the user based on the first image and the second image where the 3D model is generated based on a second machine learning model of the second machine learning architecture.

Abstract: A system includes an orientation determination system comprising a camera where the camera is configured to capture an image of an orientation feature of a physical dental model of a dental arch of a customer with material thermoformed thereon. The orientation determination system is configured to identify an offset of the physical dental model with respect to a fixture plate during positioning or before or after the physical dental model is positioned on the fixture plate by determining an actual orientation of the physical dental model based on the orientation feature. The system also includes a laser trimming system configured to cut the material along a trim line based on the identified offset while the fixture plate is moved about at least two axes to produce a dental aligner specific to the customer and being configured to reposition one or more teeth of the customer.

Abstract: A system includes one or more processors coupled to a non-transitory memory, where the one or more processors are configured to generate, using a training set comprising one or more two-dimensional (2D) training images of a dental arch and a three-dimensional (3D) dental arch model, a machine-learning model configured to generate 3D models of dental arches from 2D images of the dental arches, receive one or more 2D images of a dental arch of a user obtained by a user device of the user, and execute the machine-learning model using the one or more 2D images as input to generate a 3D model of the dental arch of the user.

Abstract: A method comprises providing an imaging system configured to acquire images of an intraoral cavity of a user where the imaging system is configured to be operable by the user by allowing the user to visually monitor the intraoral cavity while the images of the intraoral cavity are acquired. The imaging system comprises an image acquisition device configured to acquire the images, and an orientation element configured to orient the image acquisition device with respect to the intraoral cavity to facilitate acquisition of the images. The method further includes at least one of determining an oral condition of the user based on the acquired images or providing feedback based on the acquired images.

Abstract: A method for analyzing a quality of a dental aligner includes receiving, by a processor, a digital dental aligner generated based on a fabricated dental aligner. The method also includes analyzing, by the processor, the digital dental aligner to identify a quality characteristic of the fabricated dental aligner. The method also includes flagging, by the processor, the fabricated dental aligner based on the identified quality characteristic.

Abstract: A distributed system includes one or more servers configured to provide computing devices access to portals hosted by the one or more servers, where the portals include a patient intake portal accessible by a first computing device located at an office of an intake dentist or orthodontist, and an approving portal accessible by a second computing device remote from the first computing device. The distributed system includes a dental aligner fabrication system including a fabrication computing device and dental aligner fabrication equipment. The patient intake portal is configured to provide a plurality of status updates to the intake dentist or orthodontist regarding a status of the patient, where the plurality of status updates include an indication that the dental aligners have been sent to the patient.

Abstract: A system for adjusting a cutting tool includes a cutting system having a cutting tool configured to cut material thermoformed to a dental model. The cutting system is configured to determine, based on a cut line generated for the cutting tool to cut a dental aligner from the material thermoformed onto the dental model, that the cutting tool is incapable of following the cut line. The cutting system is configured to adjust a position of the cutting tool with respect to the cut line so the cutting tool is capable of following the cut line.

Abstract: Disclosed is a machine learning architecture for a two-dimensional image protocol detector configured to receive a first image representing at least a portion of a mouth of a user, and output user feedback for capturing a second image representing a portion of the mouth of the user, where the machine learning architecture outputs the user feedback in response to an image quality score of the first image not satisfying an image quality threshold.

Abstract: Systems and methods for performing a mid-course correction include receiving user compliance check information including at least one image of the user's teeth submitted by a user regarding an initial treatment plan where at least one of the images is taken by the user with a camera being external to the mouth of the user and having a dental appliance positioned at least partially within the mouth where the dental appliance holds open the user's upper and lower lips, conducting, using an intraoral scanner at an intraoral scanning site, an intraoral scan of a mouth of a user based on determining that one or more teeth of the user are not being repositioned according to the initial treatment plan, generating a corrective treatment plan based on the intraoral scan, producing a plurality of aligners based on the corrective treatment plan, and providing the plurality of aligners to the user.

Abstract: Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images include a model training system that receives data packets of a training set. Each data packet may include data corresponding to training images of a respective dental arch and a 3D training model of the respective dental arch. The model training system identifies, for a data packet, correlation points between the one or more training images and the 3D training model of the respective dental arch. The model training system generates a machine learning model using the correlation points for the data packets of the training set. A model generation system receives one or more images of a dental arch. The model generation system generates a 3D model of the dental arch by applying the images of the dental arch to the machine learning model.

Abstract: A device includes a floss assembly comprising floss wound around a spool, an insert comprising a support surface and a post configured to support the floss assembly, and a housing having a front portion and a back portion. The front portion defines a front aperture and the back portion defines a back aperture. The front aperture and the back aperture are configured to receive the insert such that the support surface interfaces with the back portion and the post interfaces with the front portion.