Abstract: A method for image-based orthodontic treatment may include receiving image data of a patient's dentition and an orthodontic appliance, identifying, from the image data, the orthodontic appliance, calculating a misalignment height of a misalignment of the orthodontic appliance with respect to the patient's dentition, determining whether the misalignment height satisfies a misalignment threshold, and in response to satisfying the misalignment threshold, providing a notification.

Abstract: Various apparatuses are disclosed (e.g., system, device, method, or the like) for guiding the capture and assessing the quality of an image, including dental images. The apparatuses may use trained neural networks to examine images and provide users feedback regarding image quality. The neural networks may be trained based on images within image groups that have been ranked based on perceived image quality.

Abstract: Provided herein are systems and methods for scoring a post-treatment tooth position of a patient's teeth. A patient's dentition may be scanned and/or segmented. Raw dental features, principal component analysis (PCA) features, and/or other features may be extracted and compared to those of other teeth, such as those obtained through automated machine learning systems. A classifier can identify and/or output the post-treatment tooth position of the patient's teeth.

Abstract: A method of dental treatment may include receiving photos of a person's dentition, identifying a stage of a treatment plan administered to the person's dentition, gathering a three-dimensional (3D) model of the person's dentition corresponding to the stage of the treatment plan, projecting attributes of the 3D model of the person's dentition onto an image plane to get a projected representation of the person's dentition at the stage of the treatment plan, comparing the photos to the projected representation to derive an error image representing the comparison, and analyzing the error image for discrepancies, wherein the discrepancies represent one or more deviations of the person's dentition from the stage of the treatment plan.

Abstract: In a technique to assess the blurriness of an image, an image of a face is received, the image including a depiction of lips. A processing device determines a region of interest in the image, wherein the region of interest comprises an area inside of the lips. The processing device applies a focus operator to the pixels within the region of interest, and calculates a sharpness metric for the region of interest using an output of the focus operator. The processing device determines whether the sharpness metric satisfies a sharpness criterion, and one or more additional operations are performed responsive to determining that the sharpness metric satisfies the sharpness criterion.

Abstract: Mercaptan-hardened epoxy polymer compositions, methods of making the mercaptan-hardened epoxy polymer compositions, and methods of using the mercaptan-hardened epoxy polymer compositions are provided. The mercaptan-hardened epoxy polymer can be produced by contacting a thiol ester composition and an epoxide composition to produce a mixture and then heating the mixture to produce the mercaptan-hardened epoxy polymer. In some embodiments, the thiol ester compositions include thiol esters, hydroxy thiol esters, and crosslinked thiol esters. Adhesive polymer compositions, methods of making the adhesive polymer compositions, and methods of using the adhesive polymer compositions are provided. The adhesive polymer composition can be produced by contacting a thiol ester composition and an epoxide composition to produce a mixture and then heating the mixture to produce the adhesive polymer composition.