Retinal Vessel Local Tortuosity under a Macula-to-Optic Disc Central-Framing Change.

Some ocular and cardiovascular diseases can be detected through the increased tortuosity of retinal blood vessels. Objective tortuosity measures can be obtained from digital image analysis of a retinography. This study tested a set of local tortuosity indices under a change in the frame center (macula, optic disc) of the eye fundus image. We illustrate the effects of such a change on 40 pairs of vessels evaluated with eight tortuosity indices. We show that the frame center change caused significant differences in the mean values of the vast majority of the tortuosity indices analyzed. The index defined as the ratio of the curvature to the arc length of a vessel segment proved to be the most robust in relation to a frame center change. Experimental results obtained from the analysis of clinical images are provided and discussed.

Indicators of progressive corneal exposure to dry eye conditions.

PURPOSE: To establish the main indicator of progressive corneal exposure to dry eye conditions in an animal model. METHODS: Cell surface covered by microvilli (SCM), intercellular junctions (IJs), cell area, cell shape, and cell shade were measured in 988 epithelial corneal cells from rabbit eyes that were kept open for different drying times (DT) between 0 and 3 h. Two multivariate logistic regressions were used to model the relationship between these morphometric cell characteristics and DT. To corroborate the results, terminal differentiation was assessed by cluster analysis. RESULTS: Scanning electron microscopy images of the epithelial cells showed typical desiccation changes that increased in frequency and intensity as DT were prolonged. Binomial logistic regression, to distinguish cells exposed to desiccation from the control cells, displayed SCM, IJ, and cell shade as significant indicators (p < 0.01) of desiccation exposure. Multinomial logistic regression analysis showed SCM, IJ, cell shade, and cell area as significant indicators (p < 0.01) differentiating the four levels of desiccation exposure, and SCM was the variable that showed elevated odds ratio in all the analysis. In addition, the cells were grouped in three groups (G1, G2, and G3) by cluster analysis. G2 cells increased in percentage as DT grew (p < 0.05, χ2 test) in detriment of G1 cells, while the percentage of G3 cells remained stable. These changes were consistent with a terminal differentiation process from G1 cells to G2 cells, which was the group with the lowest values of SCM (p < 0.001, Mann-Whitney test). CONCLUSIONS: The variable SCM could be the best determining indicator of progressive corneal exposure to dry eye conditions. The development of clinical methods to analyze microvilli density could allow a more accurate assessment of the level of degradation of the corneal epithelium under evaporative conditions.

Contact lens case cleaning procedures affect storage solution pH and osmolality.

PURPOSE: To investigate pH and osmolality changes in the solutions stored in contact lens (CL) cases, when different case rinsing and drying methods are used on a daily basis. METHODS: Four multipurpose solutions (Opti-Free Express, Solo-Care Aqua, Re-Nu Multiplus, and Complete) and two hydrogen peroxide systems (AOsept and Oxysept) were studied. Cases were filled with the solutions and kept sealed. After 8 h, the cases underwent different rinsing (rinsing; non-rinsing) and drying (air drying-AD; lint-free tissue drying-LFTD; non-drying-ND) procedures on a daily basis. Five cases of each rinsing/drying combination for each solution were evaluated. The pH and osmolality of the case-contained solution were evaluated on the 1st, 7th, 15th, and then, 30th day. RESULTS: pH and osmolality increased significantly from day 1 to 30, except for Complete in which a significant decrease in pH was found. Rinsing vs. non-rinsing CL cases did not have any influence on the pH or osmolality, except for Oxysept, which showed a significantly higher osmolality value when cases were not rinsed. However, the drying procedure did influence both measurements; pH was significantly higher in the AD compared with the ND group (p < 0.05), and there was a significant difference in osmolality between the three drying conditions (p < 0.05), with the AD group showing the highest values, and the LFTD group showing the lowest. CONCLUSIONS: Osmolality and pH values are time and drying process-dependent in a CL case cleaning schedule. Regarding drying conditions, LFTD causes less increase in osmolality. Future studies should determine whether these changes might affect bacterial growth, lens parameters, or subject comfort during CL wear.

Image processing techniques in a preliminary morphometric characterization of corneal epithelium by scanning electron microscopy.

Several processing techniques of digital images allowed us to quantify the percentage of cell surface covered by microprojections (microvilli or microplicae) (SCM), the adhesion between epithelial cells by the parameter intercellular junctions (IJ), the size (cell area), shape (cell shape) and shade (cell shade) of cells on the corneal epithelium of nine rabbits. The data were analyzed and the epithelial cells were classified into three groups by cluster analysis. Assuming the representativeness of the sample, our findings suggest that for a normal corneal epithelium, 80% of the cells could show SCM >41%, and IJ >0.98 (being one a cell to cell junction without disruptions). Standard deviations of cell shade lower than 21 gray levels could indicate a tendency to lose the cell shade mosaic. Normal corneas could show a majority of cells (54-69%) included in group 2 with smaller mean size (80% of cells with cell area <242 µm(2)), higher SCM (80% of cells with SCM >44.83%), polygonal mean shape and brighter shade. Group 1 (15-30% of cells) could show a larger mean size (80% of cells with cell area >494 µm(2)), lower SCM (although 80% of cells with SCM >32.61%), circular mean shape and darker electron reflex. Group 3 could display a medium mean size, higher SCM (similar to group 2), circular mean shape (similar to group 1), and brighter shade. These analyses could possibly be used to further assess the corneal response to ocular drugs, contact lens, and surgical procedures or to discriminate between pathology stages.

Unsupervised novelty detection using Gabor filters for defect segmentation in textures.

Gabor wavelets are applied to develop an unsupervised novelty method for defect detection and segmentation that is fully automatic and free of any adjustable parameter. The algorithm combines the Gabor analysis of the sample image with a statistical analysis of the wavelet coefficients corresponding to each detail. The statistical distribution of the coefficients corresponding to the defect-free background texture is calculated from the coefficient's distribution of the sample under inspection. Once the background texture features are estimated, a threshold is automatically fixed and applied to all the details, whose information is merged into a single binary output image in which the defect appears segmented from the background. The method is applicable to random, nonperiodic, and periodic textures. Since all the information to inspect a sample is obtained from the sample itself, the method is proof against heterogeneities between different samples of the material, in-plane positioning errors, scale variations, and lack of homogeneous illumination. Experimental results are presented. Some results are compared with other unsupervised methods designed for defect segmentation in periodic textures.

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.

Referenceless segmentation of flaws in woven fabrics.

The automatic segmentation of flaws in woven fabrics is achieved by applying Fourier analysis to the image of the sample under inspection, without considering any reference image. No prior information about the fabric structure or the defect is required. The algorithm is based on the structural feature extraction of the weave repeat from the Fourier transform of the sample image. These features are used to define a set of multiresolution bandpass filters, adapted to the fabric structure, that operate in the Fourier domain. Inverse Fourier transformation, binarization, and merging of the information obtained at different scales lead to the output image that contains flaws segmented from the fabric background. The whole process is fully automatic and can be implemented either optically or electronically. Experimental results are presented and discussed for a variety of fabrics and defects.

Weave-repeat identification by structural analysis of fabric images.

Two descriptions of the image of a web structure, a convolution model and an additive model, in both the spatial and frequency domains, are combined in the design of a method to extract information about the fabric structure by image analysis. The method allows the extraction of the conventional and also the minimal weave repeats, their size in terms of number of threads, their interlacing patterns, and their patterns of repetition. It is applicable to fabrics with square and nonsquare conventional weave repeat. Experimental results with image of real samples are presented and discussed.