Abstract: A machine learning model is trained to define bounding shapes around teeth in images. The machine learning model is trained by receiving a training dataset comprising a plurality of images, each image of the plurality of images comprising a face and a provided bounding shape around teeth in the image. The training dataset is input into an untrained machine learning model. The untrained machine learning model is trained based on the training dataset to generate a trained machine learning model that defines bounding shapes around teeth in images, wherein for an input image the trained machine learning model is to output a mask that defines a bounding shape around teeth of the input image, wherein the mask indicates, for each pixel of the input image, whether that pixel is inside of a defined bounding shape or is outside of the defined bounding shape.

Abstract: Described herein are methods and apparatuses to obtain an image, or a set of images, of a patient's teeth from one or more predetermined viewing angles. These methods and apparatuses may include the use an overlay comprising an outline of teeth for each predetermined viewing angle. The overlay may be used for automatically capturing, focusing and/or illuminating the teeth. Also described herein are methods and apparatuses for using a series of images of the patient's teeth including a set of predetermined views to determine if a patient is a candidate for an orthopedic procedure.