1. A computer implemented method for training a classifier to be operative as an epithelial texture classifier, the method comprising the steps of: obtaining a plurality of training micrograph areas of biopsy tissue; for each of the training micrograph areas: identifying probable locations of nuclei that form epithelia; generating a skeleton graph from the probable locations of the nuclei that form the epithelia; with a graphical user interface, manually drawing walls on the skeleton graph outside of the epithelia to divide the epithelia from one another; with the graphical user interface, manually selecting points that lie entirely inside the epithelia to generate open and/or closed geodesic paths in the skeleton graph between pairs of the selected points; and applying data obtained from points selected from the walls and the paths to a classifier to train the classifier as the epithelial texture classifier; wherein the probable locations of nuclei identified with an epithelial texture classifier are outputted as an epithelial mask and wherein the generation of the skeleton graph from the probable locations of the nuclei that form the epithelia of the sample micrograph area includes: determining a skeleton image of the epithelial mask; determining a path junction graph of the skeleton image; stopping if the path junction graph has no edges; applying to the path junction graph, the determination of the set of geodesic paths and/or loops in the skeleton graph to determine the epithelial paths and/or loops; and taking an area of a distance transform of the epithelial mask around the open and/or closed epithelial paths to determine the epithelial mask.