Epithelial structure detector and related methods

Abstract

A method for training a classifier to be operative as an epithelial texture classifier, includes obtaining a plurality of training micrograph areas of biopsy tissue and 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, manually drawing walls on the skeleton graph outside of the epithelia to divide the epithelia from one another, and 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. Data is obtained from points selected from the walls and the paths and applied to a classifier to train the classifier as the epithelial texture classifier. A method and detector for detecting epithelial structures includes applying a sample micrograph area of biopsy tissue to an epithelial texture classifier; identifying probable locations of nuclei that form epithelia of the sample micrograph area with the epithelial texture classifier, generating a skeleton graph from the probable locations of the nuclei that form the epithelia of the sample micrograph area, determining a set of open and/or closed geodesic paths in the skeleton graph of the sample micrograph area; and determining a set of the epithelial masks using the open and/or closed epithelial paths of the sample micrograph area.