1. An automated method for identifying areas of interest in optical coherence tomography (OCT) image data of an eye, said method comprising: collecting OCT image data over a plurality of transverse locations of the eye of a patient, wherein at least some of the OCT measurements are obtained at approximately the same transverse locations separated in time by a predetermined interval; processing the data to determine changes in the OCT measurements obtained at approximately the same transverse locations, said changes being associated with blood flow that occurs during the predetermined interval; generating a two-dimensional en face vasculature image from the processed data; analyzing the intensity content of the en face vasculature image to identify the size and shape of a particular area; displaying or storing the identified area, wherein the analyzing step includes: generating a histogram that includes the frequency distribution of the intensity values of pixels in the image data; estimating an intensity value between two peaks in the histogram that corresponds to a transition zone around the particular area; generating isophotes within the en face image based on the estimated intensity value; and evaluating the isophotes to identify the size and shape of the particular area.