A method includes processing an input comprising data from an intraoral image using a trained machine learning model that has been trained to classify regions of dental sites, wherein the trained machine learning model outputs a probability map comprising, for each pixel in the intraoral image, a first probability that the pixel belongs to a first dental class and a second probability that the pixel belongs to a second dental class, wherein the first dental class represents excess material, the excess material comprising material other than teeth or gums. The method further includes determining, based on the probability map, one or more pixels in the intraoral image that are classified as excess material. The method further includes hiding or removing from the intraoral image data for the one or more pixels that are classified as excess material.