Neural network-based generation and placement of tooth restoration dental appliances

A method comprising:

• receiving, at an input interface, one or more three-dimensional (3D) tooth meshes associated with a current dental anatomy of a dental restoration patient and a 3D component mesh representing a generated geometry for a dental appliance component;
• providing, by a neural network engine communicatively coupled to the input interface, the one or more 3D tooth meshes and the 3D component mesh received by the input interface as inputs to a neural network trained with training data comprising ground truth dental appliance component geometries and 3D tooth meshes of corresponding dental restoration cases;
• and
• executing, by the neural network engine, the neural network using the provided inputs to produce an updated model of the dental appliance component with respect to the current dental anatomy of the dental restoration patient.

A non-transitory computer-readable storage medium encoded with instructions that, when executed, cause one or more processors of a computing system to:

• receive, via an input interface of the computing system, one or more three-dimensional (3D) tooth meshes associated with a current dental anatomy of a dental restoration patient and a 3D component mesh representing a generated geometry for a dental appliance component;
• provide the one or more 3D tooth meshes and the 3D component mesh received via the input interface as inputs to a neural network trained with training data comprising ground truth dental appliance component geometries and 3D tooth meshes of corresponding dental restoration cases;
• and
• execute the neural network using the provided inputs to produce an updated model of the dental appliance component with respect to the current dental anatomy of the dental restoration patient.