Abstract: Methods and apparatuses can include generating computer 3D models of an object, by registering two or more scans of physical models of an object. The scans may be 3D scans registered by a curve-based registration process. A method can include generating a 3D model of a portion of a patient's oral anatomy that can be used in dental restoration design. Scanning workflows can include scanning physical models of an object to obtain a 3D model. A scanner can scan physical models of a patient's dentition to obtain scans used to generate a 3D model of a patient's dentition.

Abstract: A method and system receives a 3D digital dental model representing at least a portion of a patient's dentition, automatically determines a virtual dental preparation site in the 3D digital dental model using a first neural network, automatically generates a 3D digital dental prosthesis model in the 3D digital dental model using a second trained generative deep neural network and automatically routes the 3D digital dental model comprising the virtual 3D dental prosthesis model to a quality control (“QC”) user.

Abstract: A computer-implemented method and system of virtual dental restoration design automation includes: receiving a 3D virtual dental model of at least a portion of a patient's dentition, the 3D virtual dental model comprising at least one virtual preparation tooth, the virtual preparation tooth comprising a digital representation of a physical preparation tooth prepared by a dentist; performing an automated virtual restoration design using the 3D virtual dental model; displaying virtually to the dentist one or more physical preparation tooth issues detected while performing the automated virtual restoration design; and displaying virtually to the dentist a generated virtual restoration for one or more adjustments where no physical preparation tooth issues are detected while performing the automated virtual restoration design.

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 computer-implemented method/system of determining a trim-line includes receiving a 3D digital dental model; combining the one or more virtual teeth; determining a distance field; determining a first iso-line; determining a back distance field; determining a second iso-line to generate a trim-line. A computer-implemented method/system of segmenting the 3D digital dental model includes receiving a 3D digital dental model; determining an initial virtual tooth location of one or more virtual teeth; constructing a virtual crown line; determining a long axis of one or more virtual teeth; constructing a virtual root line; determining a virtual tooth virtual bounding box; performing an initial segmentation; performing final segmentation.

Abstract: Methods and apparatus are provided for generating computer 3D models of an object, by registering two or more scans of physical models of an object. The scans may be 3D scans registered by a curve-based registration process. A method is provided for generating a 3D model of a portion of a patient's oral anatomy for use in dental restoration design. Also provided are scanning workflows for scanning physical models of an object to obtain a 3D model. A scanner is provided for scanning physical models of a patient's dentition to obtain scans for generating a 3D model of a patient's dentition.

Abstract: A computer-implemented method/system/instructions of automatic margin line proposal includes receiving a 3D digital model of at least a portion of a jaw, the 3D digital model including a digital preparation tooth; determining, using a first trained neural network, an inner representation of the 3D digital model; and determining, using a second trained neural network, a margin line proposal from a base margin line and the inner representation of the 3D digital model.

Abstract: Methods and apparatus are provided for generating computer 3D models of an object, by registering two or more scans of physical models of an object. The scans may be 3D scans registered by a curve-based registration process. A method is provided for generating a 3D model of a portion of a patient's oral anatomy for use in dental restoration design. Also provided are scanning workflows for scanning physical models of an object to obtain a 3D model. A scanner is provided for scanning physical models of a patient's dentition to obtain scans for generating a 3D model of a patient's dentition.

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 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 methods of designing dental restorations and systems for performing the described methods are provided. In an embodiment, a method includes providing a virtual three dimensional representation of at least a portion of the patient's dentition that includes at least one preparation tooth, identifying a preparation margin on the virtual three dimensional representation, placing an arch form of a virtual tooth library in alignment with the virtual three dimensional representation, and proposing an initial restoration design based upon a tooth design obtained from the virtual tooth library.

Abstract: Computer-implemented methods of designing dental restorations and systems for performing the described methods are provided. In an embodiment, a method includes providing a virtual three dimensional representation of at least a portion of the patient's dentition that includes at least one preparation tooth, identifying a preparation margin on the virtual three dimensional representation, placing an arch form of a virtual tooth library in alignment with the virtual three dimensional representation, and proposing an initial restoration design based upon a tooth design obtained from the virtual tooth library.

Abstract: Computer-implemented methods for generating a 3D dental prosthesis model are disclosed herein. The methods comprise training a deep neural network to generate a first 3D dental prosthesis model using a training data set; receiving a patient scan data representing at least a portion of a patient's dentition; and generating, using the trained deep neural network, the first 3D dental prosthesis model based on the received patient scan data.

Abstract: Computer-implemented methods for generating a 3D dental prosthesis model are disclosed herein. The methods comprise training a deep neural network to generate a first 3D dental prosthesis model using a training data set; receiving a patient scan data representing at least a portion of a patient's dentition; and generating, using the trained deep neural network, the first 3D dental prosthesis model based on the received patient scan data.

Abstract: A computer-aided design (CAD) model of an article for manufacture, together with user problem definition input including materials, constraints, load conditions, preferred manufacturing processes, etc. for an optimized design of the article or material microstructure are received via a prompt-and-response graphical user interface. Based on this information, one or more routines to iteratively optimize material distribution within said article or the material microstructure design are executed in order to achieve best performance for materials, loads, and constraints specified by the user. At the completion of the optimization process, the user is presented the optimized design in a CAD file describing the optimized design of the article for the preferred manufacturing process or a newly designed material microstructure, as appropriate.

Abstract: Computer-implemented methods for generating a 3D dental prosthesis model are disclosed herein. The methods comprise training a deep neural network to generate a first 3D dental prosthesis model using a training data set; receiving a patient scan data representing at least a portion of a patient's dentition; and generating, using the trained deep neural network, the first 3D dental prosthesis model based on the received patient scan data.

Abstract: A method for compact and descriptive representation of teeth shape (or other anatomic shapes) in terms of characteristic curves and its application to generation of automatic designs within dental CAD software or other software is provided. In an embodiment, a method includes capturing tooth shape by a network of characteristic curves (i.e. margin lines). In an embodiment, a method includes compactly encoding curves as strings, which then can be indexed and searched efficiently by similarity. In an embodiment, a method includes retrieving high quality crown design proposals from a case repository based on similarity of margin lines.

Abstract: Methods and apparatus are provided for generating computer 3D models of an object, by registering two or more scans of physical models of an object. The scans may be 3D scans registered by a curve-based registration process. A method is provided for generating a 3D model of a portion of a patient's oral anatomy for use in dental restoration design. Also provided are scanning workflows for scanning physical models of an object to obtain a 3D model. A scanner is provided for scanning physical models of a patient's dentition to obtain scans for generating a 3D model of a patient's dentition.

Abstract: A method for compact and descriptive representation of teeth shape, or other shapes, in terms of characteristic curves and its application to generation of automatic designs within dental CAD software or other software is provided. In an embodiment, a method includes capturing tooth shape by a network of characteristic curves, such as margin lines. In an embodiment, a method includes compactly encoding curves as strings, which then can be indexed and searched efficiently by similarity. In an embodiment, a method includes retrieving high quality crown design proposals from a case repository based on similarity of margin line.