Image processing techniques to quantify microprojections on outer corneal epithelial cells.

It is widely accepted that cellular microprojections (microvilli and/or microplicae) of the corneal surface are essential to maintain the functionality of the tissue. To date, the characterization of these vital structures has been made by analysing scanning or transmission electron microscopy images of the cornea by methods that are intrinsically subjective and imprecise (qualitative or semiquantitative methods). In the present study, numerical data concerning three microprojection features were obtained by an automated method and analysed to establish which of them showed less variability. We propose that the most stable microprojection characteristic would be a useful sign in early detection of epithelial damage or disease. With this aim, the scanning electron microscopy images of 220 corneal epithelial cells of nine rabbits were subjected to several image processing techniques to quantify microprojection density, microprojection average size and surface covered by microprojections (SCM). We then assessed the reliability of the methods used and performed a statistical analysis of the data. Our results show that the thresholding process, the basis of all image processing techniques used in this work, is highly reliable in separating microprojections from the rest of the cell membrane. Assessment of histogram information from thresholded images is a good method to quantify SCM. Amongst the three studied variables, SCM was the most stable (with a coefficient of variation of 15.24%), as 89.09% of the sample cells had SCM values > or = 40%. We also found that the variability of SCM was mainly due to intercellular differences (the cell factor contribution represented 88.78% of the total variation in the analysed cell areas). Further studies are required to elucidate how healthy corneas maintain high SCM values.