Abstract: Techniques are described for determining bracket placement based on a cost function configured to reflect desired patient outcomes. By optimizing the cost function, positional parameters may be determined that define archwire and bracket placements that best reflect the desired outcomes. The brackets may then be arranged according to the determined positional parameters, and models for additive fabrication of the brackets may be generated. As a result, bracket placements that match desired patient outcomes may be more accurately and more efficiently determined.

Abstract: Embodiments may provide Bite Opening Devices (BODs) that are quicker and easier to place and provide improved accuracy. For example, a method may comprise using a computer system to perform: receiving data relating to teeth and jaws of a person, identifying a hinge axis of the jaw in three dimensional space using the data relating to teeth and jaws of a person, rotating the jaw to provide a desired clearance of the teeth, placing at least one Bite Opening Device on the teeth so as to provide the desired clearance of the teeth, and generating data defining a bonding tray to fit over the teeth, the bonding tray including a void corresponding to each Bite Opening Device, the generated data defining the bonding tray to be used for manufacturing the bonding tray using additive manufacturing.

Abstract: Generating a crown model using a statistical method (such as k-means clustering, principal component analysis (PCA), or similar statistical methods) can result in a crown model that is missing sharpness details below the threshold of the statistical technique. A method is provided to add back the sharpness to the resulting model by combining a single full-featured example into the algorithms generating the statistical model. The end result is a crown model that is relatively simple to produce and manipulate in real time, yet maintains the anatomical sharpness of a natural tooth.

Abstract: A dental restorative system (10) includes a dental prosthesis (21), a support surface (13a or 30) and a cement gap (22) between those opposing surfaces. A number of dry-fit features (11) can be placed upon the support surface (13a or 30) or the prosthesis (21) such that the features (11) extend into cement gap (22). Dry-fit features (11) serve to position the prosthesis (21) during a dry-fit procedure and during subsequent cementing of the prosthesis (21) to its support surface (13a or 30).

Abstract: A flexible arch model (FAM) is computed to capture and parameterize the variations of the multiple real dental arches in a training set to reconstruct missing teeth in a patient's dental anatomy. Building the FAM includes acquiring multiple sets of digitized dental arches with a pair of maxillary (upper) and mandibular (lower) jaws in the right relative position and gathering a pre-defined set of landmark points on the occlusal surface of each arch all in the same order and same corresponding positions across multiple samples. The gathered vectors of landmark points are used to perform statistical modeling (e.g. Principal Component Analysis) to create a linear subspace of the feature points with the basis of principal components (when PCA is used) found during the procedure. An arbitrary set of landmark points on a pair of upper and lower arches can be reconstructed by a linear combination of the principal components within a reasonable range of variations captured from the training samples.

Abstract: A computer-implemented method of designing a dental restoration component, including: receiving a set of design dimensional constraints which must be satisfied for the dental restoration component; receiving a set of design parameters for the dental restoration component; receiving a definition for a penalty function which takes into account at least more than one of said design parameters and which signals a constraint being reached when the value of any of said parameters violates a constraint; and using the penalty function, assigning a value to each of said design parameters for the dental restoration component, consistent with the constraints for said component.

Abstract: A flexible arch model (FAM) is computed to capture and parameterize the variations of the multiple real dental arches in a training set to reconstruct missing teeth in a patient's dental anatomy. Building the FAM includes acquiring multiple sets of digitized dental arches with a pair of maxillary (upper) and mandibular (lower) jaws in the right relative position and gathering a pre-defined set of landmark points on the occlusal surface of each arch all in the same order and same corresponding positions across multiple samples. The gathered vectors of landmark points are used to perform statistical modeling (e.g. Principal Component Analysis) to create a linear subspace of the feature points with the basis of principal components (when PCA is used) found during the procedure. An arbitrary set of landmark points on a pair of upper and lower arch can be reconstructed by a linear combination of the principal components within a reasonable range of variations captured from the training samples.

Abstract: A method of designing a dental restoration component. A set of design dimensional constraints is defined which must be satisfied for the dental restoration component. A set of design parameters for the dental restoration component also is defined. Using at least in part a penalty function, a value is assigned to each of said design parameters for the dental restoration component, consistent with the constraints for said component, said penalty function taking into account at least more than one of said design parameters and which signals a constraint being reached when the value of any of said parameters violates a constraint.

Abstract: Generating a crown model using a statistical method (such as k-means clustering, principal component analysis (PCA), or similar statistical methods) can result in a crown model that is missing sharpness details below the threshold of the statistical technique. A method is provided to add back the sharpness to the resulting model by combining a single full-featured example into the algorithms generating the statistical model. The end result is a crown model that is relatively simple to produce and manipulate in real time, yet maintains the anatomical sharpness of a natural tooth.

Abstract: A three-dimensional-based modeling method and system designed for dentistry and related medical (and appropriate non-medical) applications. Data capture means produces a point cloud representing the three-dimensional surface of an object (e.g., dental arch). Three-dimensional recognition objects are provided, particularly within those areas in the image field that have low image definition, and particularly in such of these areas that appear in overlapping portions of at least two images, to provide the three-dimensional image processing software with position, angulation, and orientation information sufficient to enable highly accurate combining (or “stitching”) of adjoining and overlapping images. Alignment, and creation of aligned related objects or models thereof, such as maxillar and mandibular arches, is facilitated.

Abstract: A three-dimensional-based modeling method and system designed for dentistry and related medical (and appropriate non-medical) applications. Data capture means produces a point cloud representing the three-dimensional surface of an object (e.g., dental arch). Three-dimensional recognition objects are provided, particularly within those areas in the image field that have low image definition, and particularly in such of these areas that appear in overlapping portions of at least two images, to provide the three-dimensional image processing software with position, angulation, and orientation information sufficient to enable highly accurate combining (or “stitching”) of adjoining and overlapping images. Alignment, and creation of aligned related objects or models thereof, such as maxillar and mandibular arches, is facilitated.

Abstract: A three-dimensional-based modeling method and system designed for dentistry and related medical (and appropriate non-medical) applications. Data capture means produces a point cloud representing the three-dimensional surface of an object (e.g., dental arch). Three-dimensional recognition objects are provided, particularly within those areas in the image field that have low image definition, and particularly in such of these areas that appear in overlapping portions of at least two images, to provide the three-dimensional image processing software with position, angulation, and orientation information sufficient to enable highly accurate combining (or “stitching”) of adjoining and overlapping images. Alignment, and creation of aligned related objects or models thereof, such as maxillar and mandibular arches, is facilitated.

Abstract: A method of designing a dental restoration component. A set of design dimensional constraints is defined which must be satisfied for the dental restoration component. A set of design parameters for the dental restoration component also is defined. Using at least in part a penalty function, a value is assigned to each of said design parameters for the dental restoration component, consistent with the constraints for said component, said penalty function taking into account at least more than one of said design parameters and which signals a constraint being reached when the value of any of said parameters violates a constraint.

Abstract: A three-dimensional-based modeling method and system designed for dentistry and related medical (and appropriate non-medical) applications. Data capture means produces a point cloud representing the three-dimensional surface of an object (e.g., dental arch). Three-dimensional recognition objects are provided, particularly within those areas in the image field that have low image definition, and particularly in such of these areas that appear in overlapping portions of at least two images, to provide the three-dimensional image processing software with position, angulation, and orientation information sufficient to enable highly accurate combining (or “stitching”) of adjoining and overlapping images. Alignment, and creation of aligned related objects or models thereof, such as maxillar and mandibular arches, is facilitated.