Various methods and systems for improved anterior segment optical coherence tomography (OCT) imaging are described. One example method includes collecting a set of OCT data of the cornea of the eye； segmenting the set of OCT data to identify one or more corneal layers； fitting a two-dimensional model of corneal surfaces to the one or more corneal layers； determining motion-correction parameters by minimizing error between the one or more corneal layers and the two-dimensional model of the corneal surfaces； and creating a motion-corrected corneal image dataset from the set of OCT data using the motion-correction parameters. The motion-corrected corneal image dataset can be used to create a model of the anterior and/or posterior surfaces of the cornea. The model of the cornea is used to generate high density and motion-artifact free epithelial thickness maps, which are used for identifying or quantifying pathology such as keratoconus.
