Method and Decision Support Subsystem for Mueller-Matrix Laser Polarization Diagnosis of Biological Tissues

Abstract

A method and decision support subsystem based on the principles of fuzzy logic for Mueller-matrix polarization diagnostics of biological tissues have been developed. On the basis of statistical, correlation and spectral analysis of invariant Muller-matrix images of biological tissues and their superpositions, informative signs of diagnosis are determined. Mathematical models of functions belonging to the "normal" and "pathology" states of the studied samples for the decisive rule in the system have been developed.