Abstract: A method of performing automated defect detection of a dental appliance comprises: generating a plurality of images of a dental appliance from different viewpoints; processing the plurality of images to determine one or more defect estimations, wherein each defect estimation is associated with a confidence score; determining whether the dental appliance has one or more defects based on the one or more defect estimations; responsive to determining that the dental appliance has one or more defects, determining, from among images of the plurality of images depicting at least one defect of the one or more defects, an image associated with a highest confidence score for the at least one defect; and displaying the determined image with the at least one defect marked thereon.

Abstract: A method of automated defect detection of a dental appliance comprises receiving a plurality of images of the dental appliance, and processing the plurality of images by a processing device to determine one or more defect estimations. The method comprises processing one or more sets of defect estimations to determine one or more defect classifications, wherein each set of the one or more sets comprises the one or more defect estimations associated with a subset of the plurality of images. The method comprises determining whether the dental appliance has a defect based on the one or more defect classifications associated with the one or more sets of defect estimations.

Abstract: A method of automated defect detection of a dental appliance comprises receiving a plurality of images of the dental appliance, and processing the plurality of images by a processing device to determine one or more defect estimations. The method comprises processing one or more sets of defect estimations to determine one or more defect classifications, wherein each set of the one or more sets comprises the one or more defect estimations associated with a subset of the plurality of images. The method comprises determining whether the dental appliance has a defect based on the one or more defect classifications associated with the one or more sets of defect estimations.