Abstract: A computer-implemented method of processing a digital dental impression includes determining one or more first digital surface regions visible from a first side of the digital dental impression along an occlusion axis and one or more second digital surface regions visible from a second side of the digital dental impression along the occlusion axis, segmenting the digital dental impression into one or more digital segments and determining the one or more digital segments as a first digital segment or a second digital segment based on the majority of digital surface regions in the one or more digital segments.

Abstract: Methods for volume manufacturing of a plurality of unique items are provided. In some embodiments, a method includes: (a) initiating a predefined fabrication processing time period, (b) retrieving a fabrication data package containing manufacturing data, (c) verifying the fabrication data package for accuracy and completeness of the manufacturing data contained therein, and (d) performing at least one fabrication process in accordance with the manufacturing data contained in the fabrication data package. If the predefined fabrication time period has not expired, the method can include repeating (b) through (d). If the predefined fabrication time period has expired, the method can include generating a status report.

Abstract: A system and method can determine one or more CT scanner calibration parameters from a plurality of calibration object projections in a plurality of radiographs.

Abstract: Systems and methods are provided for scanning a dental impression to obtain a digital model of a patient's dentition as an input to computer aided design (CAD) and computer aided manufacturing (CAM) methods for producing dental prostheses.

Abstract: A system and method include performing digital block-out of one or more digital preparation teeth.

Abstract: A computer-implemented method and system of automatically detecting and removing extraneous material from a digital dental impression includes detecting one or more dental features in a digital dental impression, filtering the one or more dental features, digitally joining the one or more dental features, and determining one or more regions of interest from the joined one or more digital dental features.

Abstract: Computer-implemented method and system automatically detects an out-of-view CT scan by receiving a voxel density file, determining a threshold iso-value of density between air density and a material density of one or more scanned objects in the voxel density file, and evaluating, using the threshold iso-value of density, one or more horizontal slices of the voxel density file to determine whether at least a portion of the one or more scanned objects is out of view.

Abstract: A system and method include digitally determining a virtual insertion path of a digital dental restoration.

Abstract: A computer-implemented method and system of determining a material surface from a volumetric density file includes generating a density frequency distribution of a volumetric density file of a dental impression and determining an iso-value of density between air and a particular material in the density frequency distribution. A computer-implemented method and system of creating a digital model from a CT scan of a physical dental impression includes selecting an iso-value of density for a digital volumetric density file having one or more voxels, generating one or more digital surface points in virtual 3D space for each of one or more voxels, and selecting a subset of digital surface points from the one or more digital surface points. A computer-implemented method and system of optimizing a digital surface includes moving one or more digital surface points to satisfy a criteria of optimum digital surface selection.

Abstract: A computer-implemented method of recognizing dental information associated with a dental model of dentition includes training a deep neural network to map a plurality of training dental models representing at least a portion of each one of a plurality of patients' dentitions to a probability vector including probability of the at least a portion of the dentition belonging to each one of a set of multiple categories. The category of the at least a portion of the dentition represented by the training dental model corresponds to the highest probability in the probability vector. The method includes receiving a dental model representing at least a portion of a patient's dentition and recognizing dental information associated with the dental model by applying the trained deep neural network to determine a category of the at least a portion of the patient's dentition represented by the received dental model.

Abstract: A computer-implemented method and system of digitally segmenting teeth in a digital model comprises generating a panoramic image from a 3D digital model of a patient's dentition, labeling, using a first trained neural network, the panoramic image to provide a labeled panoramic image, mapping the labeled panoramic image to corresponding coarse digital surface triangle labels in the 3D digital model to provide a labeled 3D digital model, and segmenting the labeled 3D digital model to provide a segmented 3D digital model. A computer-implemented method and system of generating a panoramic image comprises determining, using a trained neural network, digital tooth bounding region(s) corresponding to digital teeth from a 2D depth map of a patient's dentition, connecting digital tooth bounding region(s) by a spline, determining sampled digital surface points from the sampled spline points; and determining associated digital surface points corresponding to each sampled digital surface point.

Abstract: A system and method of processing a CT scan includes receiving a plurality of radiographs and determining an axis of rotation per scan from the plurality of radiographs prior to CT reconstruction.

Abstract: A computer-implemented method of recognizing dental information associated with a dental model of dentition includes training a deep neural network to map a plurality of training dental models representing at least a portion of each one of a plurality of patients' dentitions to a probability vector including probability of the at least a portion of the dentition belonging to each one of a set of multiple categories. The category of the at least a portion of the dentition represented by the training dental model corresponds to the highest probability in the probability vector. The method includes receiving a dental model representing at least a portion of a patient's dentition and recognizing dental information associated with the dental model by applying the trained deep neural network to determine a category of the at least a portion of the patient's dentition represented by the received dental model.

Abstract: Computer-implemented method and system automatically detects an out-of-view CT scan by receiving a voxel density file, determining a threshold iso-value of density between air density and a material density of one or more scanned objects in the voxel density file, and evaluating, using the threshold iso-value of density, one or more horizontal slices of the voxel density file to determine whether at least a portion of the one or more scanned objects is out of view.

Abstract: A computer-implemented method and system of determining a bite setting include receiving first and second digital jaw models, determining a rough bite approximation of the first and second digital jaw models, determining one or more initial bite positions of the first and second digital jaw models from the rough approximation, determining one or more iterative bite positions of the first and second digital jaw models for each of the one or more initial bite positions, determining a score for each iterative bite position, and outputting the bite setting based on the score.

Abstract: A system and method of processing a CT scan includes receiving a plurality of radiographs and determining an axis of rotation per scan from the plurality of radiographs prior to CT reconstruction.

Abstract: A computer-implemented method of designing a dental restoration at a display includes providing a virtual three dimensional representation of at least a portion of the patient's dental situation. The method includes displaying a virtual three dimensional dental restoration model in an alignment with the virtual three dimensional representation. The method also includes providing a design tool selectable to deform at least a portion of the three dimensional dental restoration model. The design tool, when selected, enables a line to be drawn on a surface of the three dimensional dental restoration model.

Abstract: A system and method can determine one or more CT scanner calibration parameters from a plurality of calibration object projections in a plurality of radiographs.

Abstract: A system and method include digitally determining a virtual insertion path of a digital dental restoration,

Abstract: A system and method include performing digital block-out of one or more digital preparation teeth.