Abstract: A method including: obtaining a plurality of images in which front teeth of a subject are visible; performing segmentation on selected images from the plurality of images to create a first segmentation mask and labeling each tooth in the selected images to provide a detailed segmentation map; generating a depth map of the front teeth; calculating a horizontal gradient of the depth map and a vertical moving average of a plurality of pixels of the horizontal gradient to receive depth gradients and flagging depth gradients where the vertical moving average exceeds a predefined threshold or is classified by an Artificial Neural Network or other machine learning model as abnormal; inputting the depth gradients and detailed segmentation map into a classifier to determine whether the front teeth are within predetermined parameters; and receiving a go or no-go classification from the classifier.