Abstract: Techniques are described for automating the design of dental restoration appliances using neural networks. An example computing device receives transform information associated with a current dental anatomy of a dental restoration patient, provides the transform information associated with the current dental anatomy of the dental restoration patient as input to a neural network trained with transform information indicating placement of a dental appliance component with respect to one or more teeth of corresponding dental anatomies, the dental appliance being used for dental restoration treatment for the one or more teeth, and executes the neural network using the input to produce placement information for the dental appliance component with respect to the current dental anatomy of the dental restoration patient.

Abstract: A custom tool for forming a dental restoration in a mouth of a patient includes a first mold body providing for a customized fit with at least one tooth of the patient. The first mold body includes a portion corresponding with at least a first surface of the tooth and an interproximal portion corresponding with an interproximal surface of the tooth, the interproximal portion being of unitary construction. The first mold body is configured to combine with the tooth of the patient to form a mold cavity encompassing a first portion of missing tooth structure of the tooth.

Abstract: A custom tool for bonding orthodontic appliances in a mouth of a patient, the custom tool comprising: a facial body for a patient-specific, customized fit with the facial side of a plurality of teeth of the patient, a lingual body for a patient-specific, customized fit with the lingual side of the plurality of the teeth of the patient, wherein the lingual body. wherein the facial body and lingual body are configured to combine with the teeth of the patient to position orthodontic appliances on the plurality of teeth.

Abstract: Machine learning, or geometric deep learning, applied to various dental processes and 5 solutions. In particular, generative adversarial networks apply machine learning to smile design—finished smile, appliance rendering, scan cleanup, restoration appliance design, crown and bridges design, and virtual debonding. Vertex and edge classification apply machine learning to gum versus teeth detection, teeth type segmentation, and brackets and other orthodontic hardware. Regression applies machine learning to coordinate systems, diagnostics, case complexity, and 0 prediction of treatment duration. Automatic encoders and clustering apply machine learning to grouping of doctors, or technicians, and preferences.

Abstract: In some examples, a tool for forming a dental restoration comprises a preformed mold body configured to provide a patient-specific, customized fit with at least one tooth to be restored of a patient. The mold body is configured to align with a portion of a surface of the at least one tooth, and is configured to combine with the at least one tooth to define a mold cavity encompassing at least a portion of desired tooth structure of the at least one tooth to be restored of the patient. The portion of desired tooth structure defines a transition from a supragingival surface of the at least one tooth to a subgingival surface of the at least one tooth.

Abstract: A tool for forming a dental restoration includes a mold body configured to provide a customized fit with at least one tooth of a patient. In some examples, the mold body defines an aperture configured to align with a portion of a surface of a tooth. The aperture is sufficiently large to allow placement and flow of restorative material over the desired portion of the surface of the tooth to be restored. The mold body is configured to combine with the at least one tooth of the patient to define a mold cavity encompassing at least a portion of desired tooth structure of the tooth to be restored.

Abstract: Techniques are described for automating the design of dental restoration appliances using neural networks. An example computing device receives transform information associated with a current dental anatomy of a dental restoration patient, provides the transform information associated with the current dental anatomy of the dental restoration patient as input to a neural network trained with transform information indicating placement of a dental appliance component with respect to one or more teeth of corresponding dental anatomies, the dental appliance being used for dental restoration treatment for the one or more teeth, and executes the neural network using the input to produce placement information for the dental appliance component with respect to the current dental anatomy of the dental restoration patient.

Abstract: A custom tool for bonding orthodontic appliances in a mouth of a patient, the custom tool comprising: a facial body for a patient-specific, customized fit with the facial side of a plurality of teeth of the patient, a lingual body for a patient-specific, customized fit with the lingual side of the plurality of the teeth of the patient, wherein the lingual body. wherein the facial body and lingual body are configured to combine with the teeth of the patient to position orthodontic appliances on the plurality of teeth.

Abstract: A custom tool for forming a dental restoration in a mouth of a patient includes a mold body providing for a customized fit with at least one tooth of the patient. The mold body includes a facial portion forming a facial surface corresponding with a facial surface of the tooth, and a separate lingual portion forming a lingual surface corresponding with a lingual surface of the tooth. The mold body is configured to combine with the tooth of the patient to form a mold cavity encompassing missing tooth structure of the tooth.

Abstract: A custom tool for bonding orthodontic appliances in a mouth of a patient, the custom tool comprising: a facial body for a patient-specific, customized fit with the facial side of a plurality of teeth of the patient, a lingual body for a patient-specific, customized fit with the lingual side of the plurality of the teeth of the patient, wherein the lingual body. wherein the facial body and lingual body are configured to combine with the teeth of the patient to position orthodontic appliances on the plurality of teeth.

Abstract: A tool for forming a dental restoration includes a mold body configured to provide a customized fit with at least one tooth of a patient. In some examples, the mold body defines an aperture configured to align with a portion of a surface of a tooth. The aperture is sufficiently large to allow placement and flow of restorative material over the desired portion of the surface of the tooth to be restored. The mold body is configured to combine with the at least one tooth of the patient to define a mold cavity encompassing at least a portion of desired tooth structure of the tooth to be restored.

Abstract: An additively manufactured dental crown with a wall having a bottom edge and an occlusal portion joined with the wall opposite the bottom edge. The wall and occlusal portion form an interior surface and an opposing exterior surface. By using additive manufacturing and materials for such, the dental crown can have thin walls with a thickness of less than 300 microns at the thinnest portion of it and can include fine printed features such as identifiers, internal ribs, slots, porous meshes, and retention elements.

Abstract: Techniques are described for automating the design and manufacture a dental restoration appliance for restoring the dental anatomy of a patient. For example, a system processes a digital three-dimensional (3D) model of a future (desired) dental anatomy of a patient, the future dental anatomy representing an intended shape of at least one tooth of the patient. The system includes a landmark identifier configured to automatically compute, based on the digital 3D model of the future dental anatomy of the patient, one or more landmarks of the future dental anatomy of the patient. The system also includes a custom feature generator configured to automatically generate, based on the one or more landmarks, one or more custom appliance features for a dental appliance for restoring the at least one tooth of the patient. The system further includes a memory device configured to store a digital model of the dental appliance.

Abstract: A custom tool for forming a dental restoration in a mouth of a patient includes a custom tool for forming a dental restoration in a mouth of a patient comprising: a mold body for a patient-specific, customized fit with the facial side and the lingual side of at least two adjacent teeth of the patient, and a flexible film, wherein the mold body is configured to combine with the flexible film to form a mold cavity encompassing missing tooth structure of at least one tooth to be restored.

Abstract: A method of making an adhesive is provided, including obtaining an actinic radiation-polymerizable adhesive precursor composition disposed against a surface of an actinic radiation-transparent substrate and irradiating a first portion of the actinic radiation-polymerizable adhesive precursor composition through the actinic radiation-transparent substrate for a first irradiation dosage. The method further includes irradiating a second portion of the actinic radiation-polymerizable adhesive precursor composition through the actinic radiation-transparent substrate for a second irradiation dosage. The first portion and the second portion are adjacent to or overlapping with each other and the first irradiation dosage and the second irradiation dosage are not the same. The method forms an integral adhesive having a variable thickness in an axis normal to the surface of the actinic radiation-transparent substrate.

Abstract: A method of making an adhesive is provided, including obtaining an actinic radiation-polymerizable adhesive precursor composition disposed against a surface of an actinic radiation-transparent substrate and irradiating a first portion of the actinic radiation-polymerizable adhesive precursor composition through the actinic radiation-transparent substrate for a first irradiation dosage. The method further includes irradiating a second portion of the actinic radiation-polymerizable adhesive precursor composition through the actinic radiation-transparent substrate for a second irradiation dosage. The first portion and the second portion are adjacent to or overlapping with each other and the first irradiation dosage and the second irradiation dosage are not the same. The method forms an integral adhesive having a variable thickness in an axis normal to the surface of the actinic radiation-transparent substrate.

Abstract: A custom tool for forming a dental restoration in a mouth of a patient includes a one-piece mold body providing for a customized fit with at least one tooth of the patient, the one-piece mold body including an occlusal portion forming an occlusal surface corresponding with an occlusal surface of the tooth, a mesial proximal portion forming a mesial proximal surface corresponding with a mesial proximal surface of the tooth, and a distal proximal portion forming a distal proximal surface corresponding with a distal proximal surface of the tooth. The mold body is configured to combine with the tooth of the patient to form a mold cavity encompassing missing tooth structure of the tooth. The occlusal portion, the mesial proximal portion, and the distal proximal portion are based on three-dimensional scan data of the mouth of the patient.

Abstract: A custom tool for forming a dental restoration in a mouth of a patient includes a first mold body providing for a customized fit with at least one tooth of the patient. The first mold body includes a portion corresponding with at least a first surface of the tooth and an interproximal portion corresponding with an interproximal surface of the tooth, the interproximal portion being of unitary construction. The first mold body is configured to combine with the tooth of the patient to form a mold cavity encompassing a first portion of missing tooth structure of the tooth.

Abstract: A tool for forming a dental restoration includes a mold body configured to provide a customized fit with at least one tooth of a patient. In some examples, the mold body defines an aperture configured to align with a portion of a surface of a tooth. The aperture is sufficiently large to allow placement and flow of restorative material over the desired portion of the surface of the tooth to be restored. The mold body is configured to combine with the at least one tooth of the patient to define a mold cavity encompassing at least a portion of desired tooth structure of the tooth to be restored.

Abstract: A custom tool for forming a dental restoration in a mouth of a patient includes a one-piece mold body providing for a customized fit with at least one tooth of the patient, the one-piece mold body including an occlusal portion forming an occlusal surface corresponding with an occlusal surface of the tooth, a mesial proximal portion forming a mesial proximal surface corresponding with a mesial proximal surface of the tooth, and a distal proximal portion forming a distal proximal surface corresponding with a distal proximal surface of the tooth. The mold body is configured to combine with the tooth of the patient to form a mold cavity encompassing missing tooth structure of the tooth. The occlusal portion, the mesial proximal portion, and the distal proximal portion are based on three-dimensional scan data of the mouth of the patient.