Abstract: Improvements to mathematical expression search functionality are made using an electronic document in ways unavailable with paper documents. A mathematical expression is exhibited within the document, and upon selection of a glyph within the mathematical expression, a display of different glyphs is made based on an expansion to the left, right, up, down, and/or diagonal of the selected glyph, each forming a different sub-expression. In this manner, a user can select one of the sub-expressions and load this sub-expression into memory to search the document or other documents for the selected sub-expression. The user also avoids having to enter complex mathematical symbols into a computer.

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.

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.

Abstract: A method for measuring structural entropy of cell nuclei in a histological micrograph of a biopsy tissue sample involves the steps of: obtaining a dye color map from a color image of the biopsy tissue sample; locating cell nuclei in the dye color map; and measuring structural features within small groups (cliques or paths) of cell nuclei to determine their degree of organization (or structural entropy). Also, an apparatus for measuring structural entropy of cell nuclei in a histological micrograph of a biopsy tissue sample includes a processor executing instructions for: obtaining a dye color map of the biopsy tissue sample; locating cell nuclei in the dye color map; and measuring structural features within small groups (cliques or paths) of cell nuclei to determine their degree of organization (or structural entropy).