Development, investigation, and software implementation of a new mathematical method for automated identification of the lipid layer state by images of eyelid intermarginal space

Abstract

A new mathematical method is presented for identifying the state of the lipid layer from images of the intermarginal space of human eyelids. As initial data, we use images of imprints of the intermarginal space of eyelids on a millipore filter after their staining with osmium vapor. Each image is a grey-scale photograph in which the dark regions represent imprints of the sebaceous secretions from the orifices of the excretory ducts of the meibomian glands. The proposed method is designed for extracting morphometric data from images of intermarginal space imprints. The method yields the following statistical characteristics: expectation and rootmean- square deviation of the imprint’s intensity on a line drawn and in a selected region, the imprint’s intensity along a line drawn, and variations in the imprint’s thickness. The proposed approach is based on the combined use of the techniques of mathematical morphology and mathematical statistics. The software implementation of the developed method, as well as the results of its experimental testing, are presented.